Search PubMed⌕ Search

Biomedical subjects

Jürgen Bajorath

Publications and source records attributed to Jürgen Bajorath.

At least 19 recordsLinked to original sources
PubMed2004

POT-DMC: A virtual screening method for the identification of potent hits.

A method for ligand-based virtual screening (LBVS), dynamic mapping of consensus positions (DMC), has been extended to take different potency levels of template compounds into account. This potency scaling technique is designed to tune search calculations toward the detection of increasingly potent hits. LBVS analysis of three different compound classes confirmed the ability of potency-scaled DMC (POT-DMC) to identify active database compounds with higher potency than conventional calculations.

CCR5 Receptor Antagonists↗
PubMed2004

Identification of structurally diverse growth hormone secretagogue agonists by virtual screening and structure-activity relationship analysis of 2-formylaminoacetamide derivatives.

Two molecules with known growth hormone secretagogue (GHS) agonist activity were used as templates to computationally screen approximately 80000 compounds. A total of 108 candidate compounds were selected, and five of them were found to be active in the low-micromolar range in both cell-based and direct binding assays. These compounds were structurally diverse and significantly differed from known GHS agonists. The most active compound was subjected to SAR evaluation, which slightly increased its potency and identified molecular regions important for specific GHS agonist activity.

Acetamides↗
PubMed2004

Docking and scoring in virtual screening for drug discovery: methods and applications.

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches.

Binding Sites↗
PubMed2004

Cell-based partitioning.

Partitioning techniques are widely used to classify compound sets or databases according to specific chemical or biological criteria. Partitioning is conceptually related to, yet algorithmically distinct from, conventional clustering methods and is particularly suitable for efficient processing of very large compound sets. Currently, some of the most popular partitioning approaches in the chemoinformatics field involve dimension reduction of initially defined chemistry spaces and creation of subsections of low-dimensional space for molecular classification. These subsections are often called cells. Original chemical reference spaces are generated through selection of various descriptors of molecular structure and properties. Principles and methodological aspects of dimension reduction of chemical spaces and compound partitioning in low-dimensional space are described herein.

Information Services↗
PubMed2004

Partitioning in binary-transformed chemical descriptor spaces.

Here we describe a statistically based partitioning method called median partitioning (MP), which involves the transformation of value distributions of molecular property descriptors into a binary classification scheme. The MP approach fundamentally differs from other partitioning approaches that involve dimension reduction of chemical spaces such as cell-based partitioning, since MP directly operates in original, albeit simplified, chemical space. Modified versions of the MP algorithm have been implemented and successfully applied in diversity selection, compound classification, and virtual screening. These findings have demonstrated that dimension reduction techniques, although elegant in their design, are not necessarily required for effective partitioning of molecular datasets. An attractive feature of statistical partitioning approaches such as decision tree methods or MP is their computational efficiency, which is becoming an important criterion for the analysis of compound databases containing millions of molecules.

Algorithms↗
PubMed2004

Virtual screening methods that complement HTS.

In this review, we discuss a number of computational methods that have been developed or adapted for molecule classification and virtual screening (VS) of compound databases. In particular, we focus on approaches that are complementary to high-throughput screening (HTS). The discussion is limited to VS methods that operate at the small molecular level, which is often called ligand-based VS (LBVS), and does not take into account docking algorithms or other structure-based screening tools. We describe areas that greatly benefit from combining virtual and biological screening and discuss computational methods that are most suitable to contribute to the integration of screening technologies. Relevant approaches range from established methods such as clustering or similarity searching to techniques that have only recently been introduced for LBVS applications such as statistical methods or support vector machines. Finally, we discuss a number of representative applications at the interface between VS and HTS.

Animals↗
PubMed2003

Molecular modeling and functional mapping of B7-H1 and B7-DC uncouple costimulatory function from PD-1 interaction.

B7-H1 and B7-DC are ligands for PD-1, a receptor implicated in negative regulation of T and B cell functions. These ligands, however, also costimulate T cell responses. It remains elusive whether or not costimulation is mediated through PD-1. By comparative molecular modeling and site-directed mutagenesis, we found that nonconserved residues between these ligands on the A'GFCC'C" face mediate interaction with PD-1. This indicates significant structural heterogeneity of the interactions between PD-1 and its ligands. Importantly, ligand mutants with abolished PD-1 binding capacity could still costimulate proliferation and cytokine production of T cells from normal and PD-1-deficient mice. Our results reveal unique binding characteristics of B7-H1 and B7-DC and provide direct evidence for an independent costimulatory receptor other than PD-1.

Amino Acid Sequence↗
PubMed2003

B7-H4, a molecule of the B7 family, negatively regulates T cell immunity.

We identify a B7 family molecule, B7-H4, by protein sequence analysis and comparative molecular modeling. While B7-H4 mRNA is widely distributed in mouse and human peripheral tissues, cell surface expression of B7-H4 protein is limited and shows an inducible pattern on hematopoietic cells. Putative receptor of B7-H4 can be upregulated on activated T cells. By arresting cell cycle, B7-H4 ligation of T cells has a profound inhibitory effect on the growth, cytokine secretion, and development of cytotoxicity. Administration of B7-H4Ig into mice impairs antigen-specific T cell responses whereas blockade of endogenous B7-H4 by specific monoclonal antibody promotes T cell responses. B7-H4 thus may participate in negative regulation of cell-mediated immunity in peripheral tissues.

Amino Acid Sequence↗
PubMed2003

Partitioning methods for the identification of active molecules.

The dramatically increasing number of compounds that become available for biological evaluation presents a significant challenge for database design, management, and mining. Computational approaches for screening, profiling, or filtering of large compound collections are by now widely used in pharmaceutical research. Among popular compound classification and database mining techniques, partitioning methods are computationally very efficient and particularly suitable for the analysis of increasingly large molecular databases, as they do not depend on pair-wise comparisons of compounds to assess molecular similarity or diversity. Promising applications of partitioning algorithms include diversity selection, searching for compounds with desired biological activity, or the derivation of predictive models from screening datasets. Compound partitioning is introduced here in the context of virtual screening and different partitioning methods are discussed that operate in low-dimensional or other chemical descriptor spaces, including a number of practical drug-discovery-related applications.

Algorithms↗
PubMed2002

Bio- and chemo-informatics beyond data management: crucial challenges and future opportunities.

Bio- and chemo-informatics are now thought to be crucial to the success and integration of biotechnology and drug discovery. Research in this area has expanded to go beyond data- and information-management. Here, we review exemplary areas, such as target identification and validation, virtual screening, and prediction of downstream characteristics of leads, where further research will play a key role in progressing the field.

Biotechnology↗
PubMed2002

Ligand binding sites of inducible costimulator and high avidity mutants with improved function.

Interaction between inducible costimulator (ICOS) and its ligand is implicated in the induction of cell-mediated and humoral immune responses. However, the molecular details of this interaction are unknown. We report here a mutagenesis analysis of residues in ICOS that are critical for ligand binding. A three-dimensional model of the extracellular immunoglobulin-like domain of ICOS was used to map the residues conserved within the CD28 family. This analysis identified a surface patch containing the characteristic "PPP" sequence and is conserved in human and mouse ICOS. Mutations in this region of human ICOS reduce or abolish ligand binding. Our results suggest that the ligand binding site in ICOS maps to a region overlapping yet distinct from the CD80/CD86 binding sites in CD28 and cytotoxic T lymphocyte antigen (CTLA)-4. Thus, the analysis suggests that differences in ligand binding specificity between these related costimulatory molecules have evolved by utilization of overlapping regions with different patterns of conserved and nonconserved residues. Two site-specific mutants generated in the course of our studies bound ICOS ligand with higher avidity than wild-type ICOS. An S76E mutant protein of ICOS blocked T cell costimulatory function of ICOS ligand and inhibited T cell response to allogeneic antigens superior to wild-type ICOS. Our studies thus identified critical residues involving in ICOS receptor-ligand interaction and provide new modulators for immune responses.

Amino Acid Sequence↗
PubMed2002

Methods for compound selection focused on hits and application in drug discovery.

In the context of virtual screening calculations, a multiple fingerprint-based metric is applied to generate focused compound libraries by database searching. Different fingerprints are used to facilitate a similarity step for database mining, followed by a diversity step to assemble the final library. The method is applied, for example, to build libraries of limited size for hit-to-lead development efforts. In studies designed to inhibit a therapeutically relevant protein-protein interaction, small molecular hits were initially obtained by combined fingerprint- and structure-based virtual screening and used for the design of focused libraries. We review the applied virtual screening approach and report the statistics and results of screening as well as focused library design. While the structures of lead compounds cannot be disclosed, the analysis is thought to provide an example of the interplay of different methods applied in practical lead identification.

Binding Sites↗
PubMed2002

Chemoinformatics methods for systematic comparison of molecules from natural and synthetic sources and design of hybrid libraries.

Until recently, the field of diversity and library design has more or less ignored natural products as a compound source. This is probably due to at least two reasons. First, combinatorial and reaction-based approaches have been major focal points in the early days of computational library design. In addition, a widespread view is that natural products are often highly complex and not amenable to medicinal chemistry efforts. This contribution introduces recent computational approaches to systematically analyze natural molecules and bridge the gap between natural products and synthetic chemistry programs. Large scale comparisons of natural and synthetic molecules are discussed as well as studies designed to identify 'synthetic mimics' of natural products with specific activity. In addition, a concept for the design of natural/synthetic hybrid libraries is introduced. Although research in this area is still in its early stages, an important lesson to be learned from computational analyses is that there is no need to a priori 'shy away' from natural products as a source for molecular design.

Biological Factors↗
PubMed2002

Integration of virtual and high-throughput screening.

High-throughput and virtual screening are important components of modern drug discovery research. Typically, these screening technologies are considered distinct approaches, as one is experimental and the other is theoretical in nature. However, given their similar tasks and goals, these approaches are much more complementary to each other than often thought. Various statistical, informatics and filtering methods have recently been introduced to foster the integration of experimental and in silico screening and maximize their output in drug discovery. Although many of these ideas and efforts have not yet proceeded much beyond the conceptual level, there are several success stories and good indications that early-stage drug discovery will benefit greatly from a more unified and knowledge-based approach to biological screening, despite the many technical advances towards even higher throughput that are made in the screening arena.

Drug Design↗
PubMedDate not supplied

Differential Shannon entropy analysis identifies molecular property descriptors that predict aqueous solubility of synthetic compounds with high accuracy in binary QSAR calculations.

Prediction of aqueous solubility of organic molecules by binary QSAR was used as a test case for a recently introduced entropy-based descriptor selection method. Property descriptors suitable for solubility predictions were exclusively selected on the basis of Shannon entropy calculations in molecular learning sets, not taking any other information into account. Sets of only five or 10 2D descriptors with largest entropy differences between molecules above or below a defined solubility threshold yielded consistently high prediction accuracy between 80% and 90% in binary QSAR calculations, regardless of the threshold values applied. The top five descriptors with largest differential Shannon entropy (DSE) values achieved an average prediction accuracy of 88%. These findings suggest that differences in entropy and relative information content of descriptors in compared compound data sets correlate with significant differences in physical properties and support the practical relevance of entropy-based descriptor selection routines. The study also demonstrates that binary QSAR methodology can be effectively used to classify small molecules according to aqueous solubility.

Journal Article↗