Molecular signatures from omics data: From chaos to consensus

In the past 15 years, new "omics" technologies have made it possible to obtain high-resolution molecular snapshots of organisms, tissues, and even individual cells at various disease states and experimental conditions. It is hoped that these developments will usher in a new era of personalized medicine in which an individual's molecular measurements are used to diagnose disease, guide therapy, and perform other tasks more accurately and effectively than is possible using standard approaches. There now exists a vast literature of reported "molecular signatures". However, despite some notable exceptions, many of these signatures have suffered from limited reproducibility in independent datasets, insufficient sensitivity or specificity to meet clinical needs, or other challenges. In this paper, we discuss the process of molecular signature discovery on the basis of omics data. In particular, we highlight potential pitfalls in the discovery process, as well as strategies that can be used to increase the odds of successful discovery. Despite the difficulties that have plagued the field of molecular signature discovery, we remain optimistic about the potential to harness the vast amounts of available omics data in order to substantially impact clinical practice.     

Genomics, molecular targets and the discovery of antifungal drugs

Comparative analyses of fungal genomes and molecular research on genes associated with fungal viability and virulence has led to the identification of many putative targets for novel antifungal agents. So far the rational approach to antifungal discovery, in which compounds are optimized against an individual target then progressed to efficacy against intact fungi and ultimately to infected humans has delivered no new agents. However, the approach continues to hold promise for the future. This review critically assesses the molecular target-based approach to antifungal discovery, outlines problems and pitfalls inherent in the genomics and target discovery strategies and describes the status of heavily investigated examples of target-based research.     

The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation*

ABSTRACT

Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.     

Mathematical algorithm for discovering states of expression from direct genetic comparison by microarrays

Highly specific direct genome-scale expression discovery from two biological samples facilitates functional discovery of molecular systems. Here, expression data from cDNA arrays are ranked and curve-fitted. The algorithm uses filters based on the derivatives (slopes) of the curve fits. The rules are set to (i) filter the largest number of artifactual ratios from same-to-same datasets and (ii) maximize discovery from direct comparisons of different samples. The unsupervised discovery is optimized without lowering specificity. The false discovery rates are significantly lower than other methods. The discovered states of genetic expression facilitate functional discovery and are validated by real-time RT–PCR. Better quality improves sensitivity.     

CNS Drug Design Based on Principles of Blood-Brain Barrier Transport

Abstract: Lipid-soluble small molecules with a molecular mass under a 400–600-Da threshold are transported readily through the blood-brain barrier in vivo owing to lipid-mediated transport. However, other small molecules lacking these particular molecular properties, antisense drugs, and peptide-based pharmaceuticals generally undergo negligible transport through the blood-brain barrier in pharmacologically significant amounts. Therefore, if present day CNS drug discovery programs are to avoid termination caused by negligible blood-brain barrier transport, it is important to merge CNS drug discovery and CNS drug delivery as early as possible in the overall CNS drug development process. Strategies for special formulation that enable drug transport through the blood-brain barrier arise from knowledge of the molecular and cellular biology of blood-brain barrier transport processes.     

Diversity and biogeography of marine actinobacteria

The actinomycetes, although not all the Actinobacteria, are easy to isolate from the marine environment. However, their ecological role in the marine ecosystem is largely neglected and various assumptions meant there was little incentive to isolate strains for search and discovery of new drugs. However, the marine environment has become a prime resource in search and discovery for novel natural products and biological diversity, and marine actinomycetes turn out to be important contributors. Similarly, striking advances have been made in marine microbial ecology using molecular techniques and metagenomics, and actinobacteria emerge as an often significant, sometimes even dominant, environmental clade. Both approaches - cultivation methods and molecular techniques - are leading to new insights into marine actinobacterial biodiversity and biogeography. Very different views of actinobacterial diversity emerge from these, however, and the true extent and biogeography of this are still not clear. These are important for developing natural product search and discovery strategies, and biogeography is a hot topic for microbial ecologists.     

Novel computational biology methods and their applications to drug discovery

Computational biology methods are now firmly entrenched in the drug discovery process. These methods focus on modeling and simulations of biological systems to complement and direct conventional experimental approaches. Two important branches of computational biology include protein homology modeling and the computational biophysics method of molecular dynamics. Protein modeling methods attempt to accurately predict three-dimensional (3D) structures of uncrystallized proteins for subsequent structure-based drug design applications. Molecular dynamics methods aim to elucidate the molecular motions of the static representations of crystallized protein structures. In this review we highlight recent novel methodologies in the field of homology modeling and molecular dynamics. Selected drug discovery applications using these methods conclude the review.     

Open discovery: An integrated live Linux platform of Bioinformatics tools

Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery ‐ a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD.     

Using NMR for ligand discovery and optimization

Several recent technology-driven advances in the area of NMR have rekindled an interest in the application of the technology to problems in drug discovery and development. A unique aspect of NMR is that it has applicability in broadly different areas of the drug discovery and optimization processes. NMR techniques for screening aimed at the discovery of novel ligands or low molecular weight structures for fragment-based build up procedures are being applied commonly in the industry. Application of NMR in structure-guided drug design and metabonomics are also becoming routine. We present an overview of some of the most recent NMR developments in these areas.     

Towards a molecular characterisation of pathological pathways

The dominant conceptual reductionism in drug discovery has resulted in many promising drug candidates to fail during the last clinical phases, mainly due to a lack of knowledge about the patho-physiological pathways they are acting on. Consequently, to increase the revenues of the drug discovery process, we need to improve our understanding of the molecular mechanisms underlying complex cellular processes and consider each potential drug target in its full biological context. Here, we review several strategies that combine computational and experimental techniques, and suggest a systems pathology approach that will ultimately lead to a better comprehension of the molecular bases of disease.     

生物发光及化学发光在生物医学领域中应用的进展

生物发光和化学发光在生物医学领域内的应用主要包括细胞学检测,分子生物学、卫生学检测,生物传感器、脂质过氧化检测和药物筛选等六个方面,其中细胞学检测主要是利用细胞内ＡＴＰ导致的虫荧光素酶发光进行活细胞计数,目前已实现快速、动态、单细胞分析;同时发现了一些新的与生物或化学发光有关的细胞学指标。分子生物学领域内的应用主要为报告基因和分子杂交,近年来又有人推出了生物发光实时ＤＮＡ测序技术。卫生学检测则主要     

Subtype-selective conopeptides targeted to nicotinic receptors:Concerted discovery and biomedical applications

Conus peptides that are selectively targeted to different molecular isoforms of nicotinic acetylcholine receptors (nAChRs) have been identified and characterized; several have recently been shown to have significant biomedical potential. An emerging strategy for the discovery from animal biodiversity of subtype-specific ligands for ion channel families is described in this review. Characterization of the gene family encoding a set of related ligands is required for discovery using a molecular genetics approach; when discovery is guided by a knowledge of the phylogeny of the biodiverse animal lineage being used as a source of ligands, a rational, efficient scan of the library of putative ligands becomes feasible. Together, these constitute an approach to uncover subtype-specific ligands, called “concerted discovery”; this was applied to the α-conotoxins, a family of Conus peptides generally targeted to nAChRs.     

Cell Mediated Immunity in Virus Infections

The discovery of the molecular nature of T cell-mediated immunity is reviewed in a historical context. Current approaches to understanding virus-induced inflammatory processes are described.     

Cancer Gene Discovery Using the Sleeping Beauty Transposon

Epidemiological and molecular data support the hypothesis that cancer results from a series of acquired somatic mutations. Discovering the initial mutations required for oncogenesis has long been a goal of cancer research. To date, the majority of causative mutations have been identified based on their ability to act in a dominant fashion and/or because they are activated by chromosomal translocations. Forward genetic screens are necessary for unbiased discovery of the remaining unknown oncogenic mutations. Two recent projects have demonstrated the feasibility of using the Sleeping Beauty transposon as an insertional mutagen for cancer gene discovery. In this article we discuss the history of cancer gene discovery and propose novel forward genetic screens using Sleeping Beauty transposon aimed at specific tissues and accelerating the discovery of recessive tumor suppressor genes.     

Recombinant organisms for production of industrial products

A revolution in industrial microbiology was sparked by the discoveries of ther double-stranded structure of DNA and the development of recombinant DNA technology. Traditional industrial microbiology was merged with molecular biology to yield improved recombinant processes for the industrial production of primary and secondary metabolites, protein biopharmaceuticals and industrial enzymes. Novel genetic techniques such as metabolic engineering, combinatorial biosynthesis and molecular breeding techniques and their modifications are contributing greatly to the development of improved industrial processes. In addition, functional genomics, proteomics and metabolomics are being exploited for the discovery of novel valuable small molecules for medicine as well as enzymes for catalysis. The sequencing of industrial microbal genomes is being carried out which bodes well for future process improvement and discovery of new industrial products.     

Fabrication of molecular materials using peptide construction motifs

Biotechnology has generally been associated with gene cloning and expression, genomics, high throughput drug discovery, biomedical advancement and agricultural development. That is about to change. Biotechnology will expand to encompass discovery and fabrication of biological and molecular materials with diverse structures, functionalities and utilities. The advent of nanobiotechnology and nanotechnology have accelerated this trend. Analogous to the construction of an intricate architectural structure, diverse and numerous structural motifs are used to assemble a sophisticated complex. Nature has selected, produced and evolved numerous molecular architectural motifs over billions of years for particular functions. These molecular motifs can now be used to build materials from the bottom up. Biotechnology will continue to harness nature's enormous power to benefit other disciplines and society as a whole.     

AlphaFold2 protein structure prediction: Implications for drug discovery

The drug discovery process involves designing compounds to selectively interact with their targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs are proteins. The outstanding accuracy with which recent artificial intelligence methods compile the three-dimensional structure of proteins has made protein targets more accessible to the drug design process. Here, we present our perspective of the significance of accurate protein structure prediction on various stages of the small molecule drug discovery life cycle focusing on current capabilities and assessing how further evolution of such predictive procedures can have a more decisive impact in the discovery of new medicines.