Fragment-based Drug Discovery Successful Contributions to Current Pharmacotherapeutic Agents Arsenal against Aggressive Cancers: A Mini-Review.

After a decade of approval of the drug vemurafenib in 2011, the hopeless scenario imposed by some severe cancer types has been mitigated by the magic bullets developed through fragment-based drug discovery. Moreover, this recent approach to medicinal chemistry has been successfully practiced by academic laboratories and pharmaceutical industry workflows focused on drug design with an enhanced profile for chemotherapy of aggressive tumors. This mini-review highlights the successes achieved by these research campaigns in the fruitful field of the molecular fragment paradigm that resulted in the approval of six new anticancer drugs in the last decade (2011-2021), as well as several promising clinical candidates. It is a particularly encouraging opportunity for other researchers who want to become aware of the applicability and potency of this new paradigm applied to the design and development of powerful molecular weapons in the constant war against these merciless scourges of humanity.

Current Fragment-to-lead Approaches Starting from the 7-azaindole: The Pharmacological Versatility of a Privileged Molecular Fragment.

Fragment-based drug discovery is one of the most powerful paradigms in the recent context of medicinal chemistry and is being widely practiced by academic and industrial researchers. Currently, azaindoles are among the most exploited molecular fragments in pharmaceutical innovation projects inspired by fragment-to-lead strategies. The 7-azaindole is the most prominent representative within this remarkable family of pyrrolopyridine fragments, as it is present in the chemical structure of several approved antitumor drugs and also of numerous therapeutic candidates. In this paper, a brief overview on existing proofs of concept in the literature will be presented, as well as some recent works that corroborate 7-azaindole as a privileged and pharmacologically versatile molecular fragment.

Towards the De Novo Design of HIV-1 Protease Inhibitors Based on Natural Products.

Acquired immunodeficiency syndrome (AIDS) caused by the human immunodeficiency virus (HIV) continues to be a public health problem. In 2020, 680,000 people died from HIV-related causes, and 1.5 million people were infected. Antiretrovirals are a way to control HIV infection but not to cure AIDS. As such, effective treatment must be developed to control AIDS. Developing a drug is not an easy task, and there is an enormous amount of work and economic resources invested. For this reason, it is highly convenient to employ computer-aided drug design methods, which can help generate and identify novel molecules. Using the de novo design, novel molecules can be developed using fragments as building blocks. In this work, we develop a virtual focused compound library of HIV-1 viral protease inhibitors from natural product fragments. Natural products are characterized by a large diversity of functional groups, many sp3 atoms, and chiral centers. Pseudo-natural products are a combination of natural products fragments that keep the desired structural characteristics from different natural products. An interactive version of chemical space visualization of virtual compounds focused on HIV-1 viral protease inhibitors from natural product fragments is freely available in the supplementary material.

Non-Extensive Fragmentation of Natural Products and Pharmacophore-Based Virtual Screening as a Practical Approach to Identify Novel Promising Chemical Scaffolds.

Fragment-based drug design (FBDD) and pharmacophore modeling have proven to be efficient tools to discover novel drugs. However, these approaches may become limited if the collection of fragments is highly repetitive, poorly diverse, or excessively simple. In this article, combining pharmacophore modeling and a non-classical type of fragmentation (herein called non-extensive) to screen a natural product (NP) library may provide fragments predicted as potent, diverse, and developable. Initially, we applied retrosynthetic combinatorial analysis procedure (RECAP) rules in two versions, extensive and non-extensive, in order to deconstruct a virtual library of NPs formed by the databases Traditional Chinese Medicine (TCM), AfroDb (African Medicinal Plants database), NuBBE (Nuclei of Bioassays, Biosynthesis, and Ecophysiology of Natural Products), and UEFS (Universidade Estadual de Feira de Santana). We then developed a virtual screening (VS) using two groups of natural-product-derived fragments (extensive and non-extensive NPDFs) and two overlapping pharmacophore models for each of 20 different proteins of therapeutic interest. Molecular weight, lipophilicity, and molecular complexity were estimated and compared for both types of NPDFs (and their original NPs) before and after the VS proceedings. As a result, we found that non-extensive NPDFs exhibited a much higher number of chemical entities compared to extensive NPDFs (45,355 vs. 11,525 compounds), accounting for the larger part of the hits recovered and being far less repetitive than extensive NPDFs. The structural diversity of both types of NPDFs and the NPs was shown to diminish slightly after VS procedures. Finally, and most interestingly, the pharmacophore fit score of the non-extensive NPDFs proved to be not only higher, on average, than extensive NPDFs (56% of cases) but also higher than their original NPs (69% of cases) when all of them were also recognized as hits after the VS. The findings obtained in this study indicated that the proposed cascade approach was useful to enhance the probability of identifying innovative chemical scaffolds, which deserve further development to become drug-sized candidate compounds. We consider that the knowledge about the deconstruction degree required to produce NPDFs of interest represents a good starting point for eventual synthesis, characterization, and biological activity studies.

Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence.

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.

Using a Fragment-Based Approach to Identify Alternative Chemical Scaffolds Targeting Dihydrofolate Reductase from Mycobacterium tuberculosis.

Dihydrofolate reductase (DHFR), a key enzyme involved in folate metabolism, is a widely explored target in the treatment of cancer, immune diseases, bacteria, and protozoa infections. Although several antifolates have proved successful in the treatment of infectious diseases, they have been underexplored to combat tuberculosis, despite the essentiality of M. tuberculosis DHFR (MtDHFR). Herein, we describe an integrated fragment-based drug discovery approach to target MtDHFR that has identified hits with scaffolds not yet explored in any previous drug design campaign for this enzyme. The application of a SAR by catalog strategy of an in house library for one of the identified fragments has led to a series of molecules that bind to MtDHFR with low micromolar affinities. Crystal structures of MtDHFR in complex with compounds of this series demonstrated a novel binding mode that considerably differs from other DHFR antifolates, thus opening perspectives for the development of relevant MtDHFR inhibitors.

Strategies towards expansion of chemical space of natural product-based compounds to enable drug discovery

Natural products (NPs) are an excellent source of biologically active molecules that provide many biologically biased features that enable innovative designing of synthetic compounds. NPs are characterized by high content of sp3-hybridized carbon atoms; oxygen; spiro, bridged, and linked systems; and stereogenic centers, with high structural diversity. To date, several approaches have been implemented for mapping and navigating into the chemical space of NPs to explore the different aspects of chemical space. The approaches providing novel opportunities to synthesize NP-inspired compound libraries involve NP-based fragments and ring distortion strategies. These methodologies allow access to areas of chemical space that are less explored, and consequently help to overcome the limitations in the use of NPs in drug discovery, such as lack of accessibility and synthetic intractability. In this review, we describe how NPs have recently been used as a platform for the development of diverse compounds with high structural and stereochemical complexity. In addition, we show developed strategies aiming to reengineer NPs toward the expansion of NP-based chemical space by fragment-based approaches and chemical degradation to yield novel compounds to enable drug discovery