In recent years, tools for the development of new drugs have been dramatically improved. These include genomic and proteomic research, numerous biophysical methods, combinatorial chemistry and screening technologies. In addition, early ADMET studies are employed in order to significantly reduce the failure rate in the development of drug candidates. As a consequence, the lead finding, lead optimization and development process has gained marked enhancement in speed and efficiency. In parallel to this development, major pharma companies are increasingly outsourcing many components of drug discovery research to biotech companies. All these measures are designed to address the need for a faster time to market. New screening methodologies have contributed significantly to the efficiency of the drug discovery process. The conventional screening of single compounds or compound libraries has been dramatically accelerated by high throughput screening methods. In addition, in silico screening methods allow the evaluation of virtual compounds. A wide range of new lead finding and lead optimization opportunities result from novel screening methods by NMR, which are the topic of this review article.

Drug Discovery Today

Finding strategies against the development of antibiotic resistance is a major global challenge for the life sciences community and for public health. The past decades have seen a dramatic worldwide increase in human-pathogenic bacteria that are resistant to one or multiple antibiotics. More and more infections caused by resistant microorganisms fail to respond to conventional treatment, and in some cases, even last-resort antibiotics have lost their power. In addition, industry pipelines for the development of novel antibiotics have run dry over the past decades. A recent world health day by the World Health Organization titled “Combat drug resistance: no action today means no cure tomorrow” triggered an increase in research activity, and several promising strategies have been developed to restore treatment options against infections by resistant bacterial pathogens.

Targeting Antibiotic Resistance

Computational medicinal chemistry offers viable strategies for finding, characterizing, and optimizing innovative pharmacologically active compounds. Technological advances in both computer hardware and software as well as biological chemistry have enabled a renaissance of computer-assisted “de novo” design of molecules with desired pharmacological properties. Here, we present our current perspective on the concept of automated molecule generation by highlighting chemocentric methods that may capture druglike chemical space, consider ligand promiscuity for hit and lead finding, and provide fresh ideas for the rational design of customized screening of compound libraries.

De Novo Design at the Edge of Chaos

Natural products have had an immense influence on science and have directly led to the introduction of many drugs. Organic chemistry, and its unique ability to tailor natural products through synthesis, provides an extraordinary approach to unlock the full potential of natural products. In this Review, an approach based on natural product derived fragments is presented that can successfully address some of the current challenges in drug discovery. These fragments often display significantly reduced molecular weights, reduced structural complexity, a reduced number of synthetic steps, while retaining or even improving key biological parameters such as potency or selectivity. Examples from various stages of the drug development process up to the clinic are presented. In addition, this process can be leveraged by recent developments such as genome mining, antibody-drug conjugates, and computational approaches. All these concepts have the potential to identify the next generation of drug candidates inspired by natural products.

https://onlinelibrary.wiley.com/doi/epdf/10.1002/anie.201505863

Capturing Biological Activity in Natural Product Fragments by Chemical Synthesis.

The utility of natural products for identifying anticancer agents has been highly pursued in the last decades and over 100 drug molecules in clinic are natural products or natural product-derived compounds. Natural products are believed to be able to cover unexplored chemical space that is normally not occupied by commercially available molecule libraries. However, the low abundance and synthetic intractability of natural products have limited their applications in drug discovery. Recently, the identification of biologically relevant fragments derived from biologically validated natural products has been recognized as a powerful strategy in searching new biological probes and drugs. The spirocyclic oxindoles, as privileged structural scaffolds, have shown their potential in designing new drugs. Several anticancer drug candidates such as SAR405838, RO8994, CFI-400945 and their bioisosteres are undergoing clinical trials or preclinical studies. To highlight the significant progress, we focus on illustrating the discovery of SAR405838, RO8994, CFI-400945 and their bioisosteres for cancer therapy using substructure-based strategies and discussing modes of action, binding models and preclinical data.

Natural Product-Derived Spirooxindole Fragments Serve as Privileged Substructures for Discovery of New Anticancer Agents

The de novo design of molecules from scratch with tailored biological activity is still the major intellectual challenge in chemical biology and drug discovery. Herein we validate natural-product-derived fragments (NPDFs) as excellent molecular seeds for the targeted de novo discovery of lead structures for the modulation of therapeutically relevant proteins. The application of this de novo approach delivered, in synergy with the combination of allosteric and active site binding motifs, highly selective and ligand-efficient non-zinc-binding (3: 4-{[5-(2-{[(3-methoxyphenyl)methyl]carbamoyl}eth-1-yn-1-yl)-2,4-dioxo-1,2,3,4-tetrahydropyrimidin-1-yl]methyl}benzoic acid) as well as zinc-binding (4: 4-({5-[2-({[3-(3-carboxypropoxy)phenyl]methyl}carbamoyl)eth-1-yn-1-yl]-2,4-dioxo-1,2,3,4-tetrahydropyrimidin-1-yl}methyl)benzoic acid) uracil-based MMP-13 inhibitors presenting IC50 values of 11 nM (3: LE=0.35) and 6 nM (4: LE=0.31).

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Merging allosteric and active site binding motifs : de novo generation of target selectivity and potency via natural-product-derived fragments

Matrix metalloproteinases (MMPs) play a key role in many diseases like cancer, atherosclerosis or arthritis Interest in MMP inhibition has been revitalized very recently as the knowledge on the underlying network of biological pathways is steadily growing On the basis of this new insight into the relevance of MMP-10 and MMP-13 within the MMP network and the ban of hydroxamate inhibitors from clinical development, the discovery of non-hydroxamate multitarget drugs against specific MMPs is of foremost interest Here, we disclose the discovery of a very potent and selective non-hydroxamate MMP-10/-13 inhibitor The high potency (IC50 of 31 nM [MMP-10] and 5 nM [MMP-13]) and selectivity over MMP-1, -2, -3, -7, -8, -9, -12, and -14 enable this compound to decipher disease causing MMP networks and to generate new treatment options through targeted polypharmacology

Jan Lanz

Papers

Merging allosteric and active site binding motifs : de novo generation of target selectivity and potency via natural-product-derived fragments

Targeted Polypharmacology: Discovery of a Highly Potent Non-Hydroxamate Dual Matrix Metalloproteinase (MMP)-10/-13 Inhibitor