Natural products as lead structures: chemical transformations to create lead-like libraries

In this review, we analyze and illustrate the variation of the two main lead-like descriptors [molecular weight (MW) and the partition coefficient (logP)] in the generation of libraries in which a natural product (NP) is used as the guiding structure. Despite the different approaches used to create NP-like libraries, controlling these descriptors during the synthetic process is important to generate lead-like libraries. From this analysis, we present a schematic approach to the generation of lead-like libraries that can be applied to any starting NP

Modern drug discovery technologies: opportunities and challenges in lead discovery

The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and\ud modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets.\ud Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges

Drug-like antagonists of P2Y receptors — from lead identification to drug development

P2Y receptors are expressed in virtually all cells and tissue types and mediate an astonishing array of biological functions, including platelet aggregation, smooth muscle cell proliferation, and immune regulation. The P2Y receptors belong to the G protein-coupled receptor superfamily and are composed of eight members encoded by distinct genes that can be subdivided into two groups on the basis of their coupling to specific G-proteins. Extensive research has been undertaken to find modulators of P2Y receptors, although to date only a limited number of small-molecule P2Y receptor antagonists have been approved by drug/medicines agencies. This Perspective reviews the known P2Y receptor antagonists, highlighting oral drug-like receptor antagonists, and considers future opportunities for the development of small molecules for clinical evaluation

Sobiva omaduste profiiliga ühendite tuvastamine keemiliste struktuuride andmekogudest

Keemiliste ühendite digitaalsete andmebaaside kasutuselevõtuga kaasneb vajadus leida neist arvutuslikke vahendeid kasutades sobivate omadustega molekule. Probleem on eriti huvipakkuv ravimitööstuses, kus aja- ja ressursimahukate katsete asendamine arvutustega, võimaldab märkimisväärset säästu. Kuigi tänapäevaste arvutusmeetodite piiratud võimsuse tõttu ei ole lähemas tulevikus võimalik kogu ravimidisaini protsessi algusest lõpuni arvutitesse ümber kolida, on lugu teine, kui vaadelda suuri andmekogusid. Arvutusmeetod, mis töötab teadaoleva statistilise vea piires, visates välja mõne sobiva ühendi ja lugedes mõni ekslikult aktiivseks, tihendab lõppkokkuvõttes andmekomplekti tuntaval määral huvitavate ühendite suhtes. Seetõttu on ravimiarenduse lihtsamate ja vähenõudlikkumade etappide puhul, nagu juhtühendite või ravimikandidaatide leidmine, edukalt võimalik rakendada arvutuslikke vahendeid. Selline tegevus on tuntud virtuaalsõelumisena ning käesolevasse töösse on sellest avarast ja kiiresti arenevast valdkonnast valitud mõningad suunad, ning uuritud nende võimekust ja tulemuslikkust erinevate projektide raames. Töö tulemusena on valminud arvutusmudelid teatud tüüpi ühendite HIV proteaasi vastase aktiivsuse ja tsütotoksilisuse hindamiseks; koostatud uus sõelumismeetod; leitud potentsiaalsed ligandid HIV proteaasile ja pöördtranskriptaasile; ning kokku pandud farmakokineetiliste filtritega eeltöödeldud andmekomplekt – mugav lähtepositsioon edasisteks töödeks.With the implementation of digital chemical compound libraries, creates the need for finding compounds from them that fit the desired profile. The problem is of particular interest in drug design, where replacing the resource-intensive experiments with computational methods, would result in significant savings in time and cost. Although due to the limitations of current computational methods, it is not possible in foreseeable future to transfer all of the drug development process into computers, it is a different story with large molecular databases. An in silico method, working within a known error margin, is still capable of significantly concentrating the data set in terms of attractive compounds. That allows the use of computational methods in less stringent steps of drug development, such as finding lead compounds or drug candidates. This approach is known as virtual screening, and today it is a vast and prospective research area comprising of several paradigms and numerous individual methods. The present thesis takes a closer look on some of them, and evaluates their performance in the course of several projects. The results of the thesis include computational models to estimate the HIV protease inhibition activity and cytotoxicity of certain type of compounds; a few prospective ligands for HIV protease and reverse transcriptase; pre-filtered dataset of compounds – convenient starting point for subsequent projects; and finally a new virtual screening method was developed

Consensus rank orderings of molecular fingerprints illustrate the ‘most genuine’ similarities between marketed drugs and small endogenous human metabolites, but highlight exogenous natural products as the most important ‘natural’ drug transporter substrates

We compare several molecular fingerprint encodings for marketed, small molecule drugs, and assess how their rank order varies with the fingerprint in terms of the Tanimoto similarity to the most similar endogenous human metabolite as taken from Recon2. For the great majority of drugs, the rank order varies very greatly depending on the encoding used, and also somewhat when the Tanimoto similarity (TS) is replaced by the Tversky similarity. However, for a subset of such drugs, amounting to some 10 % of the set and a Tanimoto similarity of ~0.8 or greater, the similarity coefficient is relatively robust to the encoding used. This leads to a metric that, while arbitrary, suggests that a Tanimoto similarity of 0.75-0.8 or greater genuinely does imply a considerable structural similarity of two molecules in the drug-endogenite space. Although comparatively few ( 0.75). This is referred to as the Take Your Pick Improved Cheminformatic Analytical Likeness or TYPICAL encoding, and on this basis some 66 % of drugs are within a TS of 0.75 to an endogenite. We next explicitly recognise that natural evolution will have selected for the ability to transport dietary substances, including plant, animal and microbial ‘secondary’ metabolites, that are of benefit to the host. These should also be explored in terms of their closeness to marketed drugs. We thus compared the TS of marketed drugs with the contents of various databases of natural products. When this is done, we find that some 80 % of marketed drugs are within a TS of 0.7 to a natural product, even using just the MACCS encoding. For patterned and TYPICAL encodings, 80 % and 98 % of drugs are within a TS of 0.8 to (an endogenite or) an exogenous natural product. This implies strongly that it is these exogeneous (dietary and medicinal) natural products that are more to be seen as the ‘natural’ substrates of drug transporters (as is recognised, for instance, for the solute carrier SLC22A4 and ergothioneine). This novel analysis casts an entirely different light on the kinds of natural molecules that are to be seen as most like marketed drugs, and hence potential transporter substrates, and further suggests that a renewed exploitation of natural products as drug scaffolds would be amply rewarded

Drug-like antagonists of P2Y receptors — from lead identification to drug development

P2Y receptors are expressed in virtually all cells and tissue types and mediate an astonishing array of biological functions, including platelet aggregation, smooth muscle cell proliferation, and immune regulation. The P2Y receptors belong to the G protein-coupled receptor superfamily and are composed of eight members encoded by distinct genes that can be subdivided into two groups on the basis of their coupling to specific G-proteins. Extensive research has been undertaken to find modulators of P2Y receptors, although to date only a limited number of small-molecule P2Y receptor antagonists have been approved by drug/medicines agencies. This Perspective reviews the known P2Y receptor antagonists, highlighting oral drug-like receptor antagonists, and considers future opportunities for the development of small molecules for clinical evaluation

Protein Flexibility in Structure-Based Drug Design: Method Development and Novel Mechanisms for Inhibiting HIV-1 Protease.

Structure-based drug design (SBDD) has emerged as an important tool in drug discovery research. Traditionally, SBDD is based on a static crystal structure of the target protein. However, a protein in solution exists as an ensemble of energetically accessible conformations and is best described when all states are represented. Upon ligand binding, further conformational changes in the receptor can be induced. While ligand flexibility can be accurately reproduced, replicating the innumerable degrees of freedom of the protein is impractical due to limitations in computational power. Previously, Carlson et al. developed a robust method to generate receptor-based pharmacophore models based on an ensemble of protein conformations. The use of multiple protein structures (MPS) allows a range of conformational space that can be assumed by the protein to be sampled and hence, simulates the inherent flexibility of a binding site in a computationally feasible manner. Small molecule probes are used to map energetically favorable regions of each protein active site, and the MPS are then overlaid to identify the most important, chemically relevant features conserved across the conformations. Here, we have refined the MPS method by developing techniques to optimize different steps in the procedure. First, we outline tools to properly overlay flexible proteins based on the rigid regions of the structure by incorporating a Gaussian weight into a standard RMSD alignment. Atoms that barely move between the two conformations will have a greater weighting than those that have a large displacement. Using HIV-1 protease (HIV-1p) as a test case, we next examine the use of various sources of MPS: snapshots of an apo structure across a molecular dynamics simulation, a bound NMR ensemble, and a collection of bound crystal structures. Finally, we implement a simple ranking metric into the MPS method to quantify ligand overlap with a contour-based representation of the pharmacophore model. Overlapping in a region of the active site dense with pharmacophore spheres results in a higher ranking of a ligand pose. The refined MPS method and other computational techniques are then applied to study HIV-1p and investigate a novel inhibition mechanism by modulating its conformational behavior.Ph.D.Medicinal ChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/57666/2/kdamm_1.pd

Synthesis of bespoke matrices to investigate a novel anti-tumour molecular target using affinity chromatography. The design, synthesis and evaluation of biotinylated biarylheterocycles used as novel affinity probes in the identification of anti-tumour molecular targets.

Three novel, synthetic biarylheterocycles bearing imidazole terminal groups had previously been discovered with high cytotoxicity (IC50 16¿640 nM) against a number of human tumour cell lines. Notably, this biological activity was independent of duplex DNA binding affinity. The compounds were tested in the NCI 60-cell line panel and COMPARE analysis suggests they have a novel mechanism of action, targeting the product of a ¿gene-like sequence¿ of unidentified function. The identity of likely protein targets was explored using a chemical proteomic strategy. Bespoke affinity matrices for chromatography were prepared in which test compounds were attached to a solid support through a biotin tag. A synthetic route to hit compounds containing a biotin moiety in place of one of the imidazole sidechains was developed. Chemosensitivity studies confirmed that the biotinylated compounds retained their activity showing IC50 = 6.25 ¿M in a susceptible cell line, compared with > 100 ¿M for an insensitive cell line. The biotinylated ligands were complexed to a streptavidin-activated affinity column and exposed to cell lysates from the susceptible cell lines. Bound proteins were eluted from the column and separated using SDS-PAGE. Proteins were characterised by MALDI MS and MS/MS and identified using Mascot database searches. Heterogeneous nuclear ribonuclear protein A2/B1 was found to selectively bind to the affinity probes.Yorkshire Cancer Research, BMSS, School of Life Sciences and the Frank Hudson Memorial Fun