Search

Modern drug discovery employs a 'screening funnel' to pick compounds worthy of advancing to the clinic, a multi-step process linking a series of assays. Molecules which are active in in vitro assays are passed to a cell-based assay, etc. Each pair of assays may be discordant, due to their measuring similar but not identical properties. This can create an enormous potential to overlook the best molecules, which we highlight here through an understanding of relationships we call 'hit diffusion'. Understanding hit diffusion has important implications for structure-based design, and drug discovery overall. The biophysical bases for assay discordance are outlined, and some strategies for ameliorating the hit diffusion problem are described., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The recent revolution in cryo-EM has produced an explosion of structures at near-atomic or better resolution. This has allowed cryo-EM structures to provide visualization of bound small-molecule ligands in the macromolecules, and these new structures have provided unprecedented insights into the molecular mechanisms of complex biochemical processes. They have also had a profound impact on drug discovery, defining the binding modes and mechanisms of action of well-known drugs as well as driving the design and development of new compounds. This review will summarize and highlight some of these structures. Most excitingly, the latest cryo-EM technology has produced structures at 1.2 Å resolution, further solidifying cryo-EM as a powerful tool for drug discovery. Therefore, cryo-EM will play an ever-increasing role in drug discovery in the coming years., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

In the originally published version of this Letter, the authors Arthur F. Kluge, Michael A. Patane and Ce Wang were inadvertently omitted from the author list. Their affiliations are: I-to-D, Inc., PO Box 6177, Lincoln, Massachusetts 01773, USA (A.F.K.); Mitobridge, Inc. 1030 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA (M.A.P.); and China Novartis Institutes for BioMedical Research, No. 4218 Jinke Road, Zhangjiang Hi-Tech Park, Pudong District, Shanghai 201203, China (C.W.). These authors contributed to the interpretation of results and design of compounds. In addition, author 'Edward A. Kesicki' was misspelled as 'Ed Kesicki'. These errors have been corrected online.

p300 and its paralog CBP can acetylate histones and other proteins and have been implicated in a number of diseases characterized by aberrant gene activation, such as cancer. A novel, highly selective, orally bioavailable histone acetyltransferase (HAT) domain inhibitor has been identified through virtual ligand screening and subsequent optimization of a unique hydantoin screening hit. Conformational restraint in the form of a spirocyclization followed by substitution with a urea led to a significant improvement in potency. Replacement of the hydantoin moiety with an oxazolidinedione followed by fluoro substitution led to A-485 , which exhibits potent cell activity, low clearance, and high oral bioavailability., Competing Interests: The authors declare the following competing financial interest(s): This study was sponsored by AbbVie. AbbVie contributed to the study design, research, and interpretation of data, writing, reviewing, and approving the publication. M.R.M., T.M.H., R.M.R., R.Man., H.L., K.D.B., L.L., and A.L. are employees of AbbVie. D.M., E.A.K., K.K., P.d.V., and J.W.L were employees of Acylin, which provided assets to Abbvie at the time of the study. R.Mar. and P.A.C. are co-founders of Acylin and consultants for AbbVie.

The dynamic and reversible acetylation of proteins, catalysed by histone acetyltransferases (HATs) and histone deacetylases (HDACs), is a major epigenetic regulatory mechanism of gene transcription and is associated with multiple diseases. Histone deacetylase inhibitors are currently approved to treat certain cancers, but progress on the development of drug-like histone actyltransferase inhibitors has lagged behind. The histone acetyltransferase paralogues p300 and CREB-binding protein (CBP) are key transcriptional co-activators that are essential for a multitude of cellular processes, and have also been implicated in human pathological conditions (including cancer). Current inhibitors of the p300 and CBP histone acetyltransferase domains, including natural products, bi-substrate analogues and the widely used small molecule C646, lack potency or selectivity. Here, we describe A-485, a potent, selective and drug-like catalytic inhibitor of p300 and CBP. We present a high resolution (1.95 Å) co-crystal structure of a small molecule bound to the catalytic active site of p300 and demonstrate that A-485 competes with acetyl coenzyme A (acetyl-CoA). A-485 selectively inhibited proliferation in lineage-specific tumour types, including several haematological malignancies and androgen receptor-positive prostate cancer. A-485 inhibited the androgen receptor transcriptional program in both androgen-sensitive and castration-resistant prostate cancer and inhibited tumour growth in a castration-resistant xenograft model. These results demonstrate the feasibility of using small molecule inhibitors to selectively target the catalytic activity of histone acetyltransferases, which may provide effective treatments for transcriptional activator-driven malignancies and diseases.

Proteins fold into their functional 3-dimensional structures from a linear amino acid sequence. In vitro this process is spontaneous; while in vivo it is orchestrated by a specialized set of proteins, called chaperones. Protein folding is an ongoing cellular process, as cellular proteins constantly undergo synthesis and degradation. Here emerging links between this process and cancer are reviewed. This perspective both yields insights into the current struggle to develop novel cancer chemotherapeutics and has implications for future chemotherapy discovery.

The problem of how to explore structure-activity relationships (SARs) systematically is still largely unsolved in medicinal chemistry. Recently, data analysis tools have been introduced to navigate activity landscapes and to assess SARs on a large scale. Initial investigations reveal a surprising heterogeneity among SARs and shed light on the relationship between 'global' and 'local' SAR features. Moreover, insights are provided into the fundamental issue of why modeling tools work well in some cases, but not in others.

We introduce the notion of structure-activity landscape index (SALI) curves as a way to assess a model and a modeling protocol, applied to structure-activity relationships. We start from our earlier work [ J. Chem. Inf. Model., 2008, 48, 646-658], where we show how to study a structure-activity relationship pairwise, based on the notion of "activity cliffs"--pairs of molecules that are structurally similar but have large differences in activity. There, we also introduced the SALI parameter, which allows one to identify cliffs easily, and which allows one to represent a structure-activity relationship as a graph. This graph orders every pair of molecules by their activity. Here, we introduce the new idea of a SALI curve, which tallies how many of these orderings a model is able to predict. Empirically, testing these SALI curves against a variety of models, ranging over two-dimensional quantitative structure-activity relationship (2D-QSAR), three-dimensional quantitative structure-activity relationship (3D-QSAR), and structure-based design models, the utility of a model seems to correspond to characteristics of these curves. In particular, the integral of these curves, denoted as SCI and being a number ranging from -1.0 to 1.0, approaches a value of 1.0 for two literature models, which are both known to be prospectively useful.

A new method for analyzing a structure-activity relationship is proposed. By use of a simple quantitative index, one can readily identify "structure-activity cliffs": pairs of molecules which are most similar but have the largest change in activity. We show how this provides a graphical representation of the entire SAR, in a way that allows the salient features of the SAR to be quickly grasped. In addition, the approach allows us view the SARs in a data set at different levels of detail. The method is tested on two data sets that highlight its ability to easily extract SAR information. Finally, we demonstrate that this method is robust using a variety of computational control experiments and discuss possible applications of this technique to QSAR model evaluation.

This perspectives article has been taken from a talk the author gave at the symposium in honor of Yvonne C. Martin's retirement, held at the American Chemical Society spring meeting in Chicago on March 25, 2007. The talk was intended as a somewhat lighthearted attempt to gaze into the future; inevitably, in print, things will come across more seriously than was intended. As we all know-the past is rarely predictive of the future.

We recently described the identification of an optimized alpha-ketoamide warhead for our series of HCV NS3.4A inhibitors. We report herein a series of HCV protease inhibitors incorporating 3-alkyl-substituted prolines in P(2). These compounds show exceptional enzymatic and cellular potency given their relatively small size. The marked enhancement of activity of these 3-substituted proline derivatives relative to previously reported 4-hydroxyproline derivatives constitutes additional evidence for the importance of the S(2) binding pocket as the defining pharmacophore for inhibition of the NS3.4A enzyme.

The alpha-ketoamide warhead (e.g., 15) was found to be a practical replacement for aliphatic aldehydes in a series of HCV NS3.4A protease inhibitors. Structure-activity relationships and prime side optimization are discussed.

Tetrapeptide-based peptidomimetic compounds have been shown to effectively inhibit the hepatitis C virus NS3.4A protease without the need of a charged functionality. An aldehyde is used as a prototype reversible electrophilic warhead. The SAR of the P1 and P2 inhibitor positions is discussed.

Pharmacophore discovery is one of the major elements of molecular modeling in the absence of X-ray structural data. While pharmacophores initially made their debut as a means for lead discovery, more recent refinements have brought them into the domain of lead optimization, e.g. as a means to define the molecular alignment in 3D-QSAR. In this review, the experiences of over a decade of confronting and solving the challenges of pharmacophore discovery applied to actual drug discovery are summarized. Also, practical tips are described for using the author's methodology for pharmacophore discovery, DANTE.

The active site of the catalytic domain of stromelysin-1 (matrix metalloproteinase-3, MMP-3) was probed by fluorescence quenching, lifetime, and polarization of its three intrinsic tryptophans and by the environmentally sensitive fluorescent reporter molecule bisANS. Wavelength-dependent acrylamide quenching identified three distinct emitting tryptophan species, only one of which changes its emission and fluorescence lifetime upon binding of the competitive inhibitor Batimastat. Significant changes in the tryptophan fluorescence polarization occur upon binding by any of the three hydroxamate inhibitors Batimastat, CAS108383-58-0, and Celltech CT1418, all of which bind in the P2'-P3' region of the active site. In contrast, the inhibitor CGS27023A, which is thought to bind in the P1-P1' region, does not induce any change in tryptophan fluorescence polarization. The use of the fluorescent probe bisANS revealed the existence of an auxiliary binding site extrinsic to the catalytic cleft. BisANS acts as a competitive inhibitor of stromelysin with a dissociation constant of Ki=22 microM. In addition to this binding to the active site, it also binds to the auxiliary site with a dissociation constant of 3.40+/-0.17 microM. The auxiliary site is open, hydrophobic, and near the fluorescing tryptophans. The binding of bisANS to the auxiliary site is greatly enhanced by Batimastat, but not by the other competitive inhibitors tested.

Strategies are described for constructing pharmacophoric 3D database queries, based on a series of active and inactive analogs. The results are highly selective database queries, which are consistent with the generally accepted pharmacophore for a number of systems. The foundation of these strategies is the method of Mayer, Naylor, Motoc and Marshall [J. Comput.-Aided Mol. Design, 1 (1987) 3] for inferring a unique binding geometry for angiotensin-converting enzyme (ACE) inhibitors. The strategies described here generalize their approach to cases where the chemical features responsible for binding are not a priori apparent, and to cases where the binding geometry deduced by that method is not unique. The key new insight, the selectivity principle, is to rank the multiple solutions produced by the method of Mayer et al. by their selectivity, a value that is related to the proportion of a database that is returned as a database hit list. Retrospective analyses are described for D2-antagonists, ACE inhibitors, fibrinogen antagonists, and beta 2-antagonists.

A mathematical formula is introduced for predicting the number of hits that should be observed in a flexible 3D database search, based on the results of a set of related queries. The projected number of hits is always greater than or equal to the actual number of hits, the discrepancy being due to imperfect treatment of conformational flexibility of the molecules. Hence, the difference between the projected and actual number of hits, delta, serves to measure how well conformational flexibility is being treated, in a manner that is objective, easy for a user to quickly verify, and independent of the particular algorithm for flexible 3D database search. It is shown that delta is a function both of how well conformational flexibility is treated and of the precision of the query. When the distance constraint is defined only to a precision of +/- 2.0 A, in a single-conformer database of drug-like molecules delta values of only 0.03 are found, while in a single-conformer database of di- and tripeptides, delta is 0.15. At increased precision, a flexible 3D database search becomes critical. For a single-conformer database, using a query of precision +/- 0.2 A, applied to a database of drug-like molecules, delta is 0.97; applied to a database of di- and tripeptides, delta is 2.21. By contrast, treating conformational flexibility by storing up to 100 conformers per molecule, at this precision, applied to a database of drug-like molecules, delta is 0.002; applied to a database of di- and tripeptides, delta is 0.07. This inequality, and hence delta, is defined only for database queries containing a single distance constraint; how the inequality may generalize to higher-dimensional queries is still unclear.

ALADDIN is a computer program for the design or recognition of compounds that meet geometric, steric, and substructural criteria. ALADDIN searches a database of three-dimensional structures, marks atoms that meet substructural criteria, evaluates geometric criteria, and prepares a number of files that are input for molecular modification and coordinate generation as well as for molecular graphics. Properties calculated from the three-dimensional structure are described by either properties calculated from the molecule itself or from the molecule as compared to a reference molecule and associated surfaces. ALADDIN was used to design analogues to probe a bioactive conformation of a small molecule and a peptide, to test alternative superposition rules for receptor mapping of the D2 dopamine receptor, to recognize unexpected D2 dopamine agonist activity of existing compounds, and to design compounds to fit a binding site on a protein of known structure. We have found that series designed by ALADDIN show much more subtle variation in shape than do those designed by traditional methods and that compounds can be designed to be very close matches to the objective.