生物信息学技术

Diversity has historically played a critical role in design of combinatorial libraries, screening sets and corporate collections for lead discovery. Large library design dominated the field in the 1990s with methods ranging anywhere from purely arbitrary through property based r ...

For quite some time, the majority of GPCR models have been based on a single template structure: dark-adapted bovine rhodopsin. The recent solution of β2AR, β1AR and adenosine A2A receptor crystal structures has dramatically expanded the GPCR structural landscape and provided many new in ...

This chapter surveys the literature for state-of-the-art methods for the rational design of siRNA libraries. It identifies and presents major milestones in the field of computational modeling of siRNA’s gene silencing efficacy. Commonly used features of siRNAs are summarized along w ...

The automatic perception of chemical similarities between chemical reactions is required for a variety of applications in chemistry and connected fields, namely with databases of metabolic reactions. Classification of enzymatic reactions is required, e.g., for genome-scale r ...

Computer-assisted molecular design supports drug discovery by suggesting novel chemotypes and compound modifications for lead structure optimization. While the aspect of synthetic feasibility of the automatically designed compounds has been neglected for a long time, we are ...

This chapter is a review of the most recent developments in the field of pharmacophore modeling, covering both methodology and application. Pharmacophore-based virtual screening is nowadays a mature technology, very well accepted in the medicinal chemistry laboratory. Neverth ...

The Scaffold Tree algorithm (J Chem Inf Model 47:47–58, 2007) allows to organize large molecular data sets by arranging sets of molecules into a unique tree hierarchy based on their scaffolds, with scaffolds forming leaf nodes of such tree. The hierarchy is created by iterative removal of rings from ...

Support vector machine (SVM)-based selectivity searching has recently been introduced to identify compounds in virtual screening libraries that are not only active for a target protein, but also selective for this target over a closely related member of the same protein family. In simula ...

An understanding of simple statistical techniques is invaluable in science and in life. Despite this, and despite the sophistication of many concerning the methods and algorithms of molecular modeling, statistical analysis is usually rare and often uncompelling. I present here some b ...

Molecular similarity is a pervasive concept in chemistry. It is essential to many aspects of chemical reasoning and analysis and is perhaps the fundamental assumption underlying medicinal chemistry. Dissimilarity, the complement of similarity, also plays a major role in a growing num ...

In this chapter we discuss the landscape view of structure–activity relationships (SARs). The motivation for such a view is that SARs come in a variety of forms, such as those where small changes in structure lead to small changes in activity or where small structural lead to significant changes in ac ...

This chapter reviews the use of molecular fingerprints for chemical similarity searching. The fingerprints encode the presence of 2D substructural fragments in a molecule, and the similarity between a pair of molecules is a function of the number of fragments that they have in common. Altho ...

The exploration of structure–activity relationships (SARs) is a major challenge in medicinal chemistry and usually focuses on compound potency for individual targets. However, selectivity of small molecules that are active against related targets is another critical paramet ...

Reduced graphs provide summary representations of chemical structures by collapsing groups of connected atoms into single nodes while preserving the topology of the original structures. This chapter reviews the extensive work that has been carried out on reduced graphs at The Unive ...

The identification of drug–target interactions from heterogeneous biological data is critical in the drug development. In this chapter, we review recently developed in silico chemogenomic approaches to infer unknown drug–target interactions from chemical information of dr ...

This chapter describes the Glycan Miner Tool, which is available as a part of the Resource for INformatics of Glycomes at Soka Web site. It implements the α-closed frequent subtree algorithm to find significant subtrees from within a data set of glycan structures, or carbohydrate sugar chains. T ...

Methods capable of identifying genetic pathways with coordinated expression signatures are critical to advance our understanding of the functions of biological networks. Currently, the most comprehensive and validated biological networks are metabolic networks. Compl ...

Reverse engineering the gene regulatory network is challenging because the amount of available data is very limited compared to the complexity of the underlying network. We present a technique addressing this problem through focussing on a more limited problem: inferring direct targ ...

Elucidating the structure of gene regulatory networks (GRN), i.e., identifying which genes are under control of which transcription factors, is an important challenge to gain insight on a cell’s working mechanisms. We present SIRENE, a method to estimate a GRN from a collection of expression d ...

Bayesian networks are probabilistic graphical models suitable for modeling several kinds of biological systems. In many cases, the structure of a Bayesian network represents causal molecular mechanisms or statistical associations of the underlying system. Bayesian networ ...