scholarly journals How Size Matters: Designing Diverse Fragment Libraries for Novel Drug Discovery

Proceedings ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 107
Author(s):  
Yun Shi ◽  
Mark von Itzstein
Keyword(s):  
Drug Discovery ◽  
Chemical Space ◽  
Structural Diversity ◽  
Optimal Size ◽  
Zinc Database ◽  
Fragment Library ◽  
Size Diversity ◽  
Efficient Exploration ◽  
Novel Drug ◽  
Fragment Libraries

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for both new and established therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. In order to construct a library that maximises the chances of discovering novel chemical matter, a large number of fragments with sufficient structural diversity are often sought. However, the exact diversity of a certain collection of fragments remains elusive, which hinders direct comparisons among different selections of fragments. Building upon structural fingerprints that are commonly utilised in cheminformatics, we herein introduced quantitative measures for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database and filtered by physicochemical properties, after which they were subject to selections with library sizes ranging from 100 to 100,000 compounds. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results suggested the existence of an optimal size for structural diversity and demonstrated that such quantitative measures can guide the design of diverse fragment libraries under various circumstances

scholarly journals How Size Matters: Diversity for Fragment Library Design

Molecules ◽  
2019 ◽  
Vol 24 (15) ◽  
pp. 2838 ◽  
Author(s):  
Yun Shi ◽  
Mark von Itzstein
Keyword(s):  
Chemical Space ◽  
Structural Diversity ◽  
Optimal Size ◽  
Library Size ◽  
Quantitative Metrics ◽  
Zinc Database ◽  
Fragment Library ◽  
Size Diversity ◽  
Efficient Exploration ◽  
Fragment Libraries

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximize the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

scholarly journals How Size Matters: Diversity for Fragment Library Design

2019 ◽  
Author(s):  
Yun Shi ◽  
Mark von Itzstein
Keyword(s):  
Chemical Space ◽  
Structural Diversity ◽  
Optimal Size ◽  
Library Size ◽  
Quantitative Metrics ◽  
Zinc Database ◽  
Fragment Library ◽  
Size Diversity ◽  
Efficient Exploration ◽  
Fragment Libraries

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW &lt; 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximise the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

scholarly journals Fragment Library of Natural Products and Compound Databases for Drug Discovery

Biomolecules ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1518 ◽  
Author(s):  
Ana L. Chávez-Hernández ◽  
Norberto Sánchez-Cruz ◽  
José L. Medina-Franco
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Synthetic Compounds ◽  
Drug Candidates ◽  
Compound Libraries ◽  
Chemical Database ◽  
Fragment Library ◽  
Further Development ◽  
Fragment Libraries ◽  
Fragment Based Drug Discovery

Natural products and semi-synthetic compounds continue to be a significant source of drug candidates for a broad range of diseases, including coronavirus disease 2019 (COVID-19), which is causing the current pandemic. Besides being attractive sources of bioactive compounds for further development or optimization, natural products are excellent substrates of unique substructures for fragment-based drug discovery. To this end, fragment libraries should be incorporated into automated drug design pipelines. However, public fragment libraries based on extensive collections of natural products are still limited. Herein, we report the generation and analysis of a fragment library of natural products derived from a database with more than 400,000 compounds. We also report fragment libraries of a large food chemical database and other compound datasets of interest in drug discovery, including compound libraries relevant for COVID-19 drug discovery. The fragment libraries were characterized in terms of content and diversity.

scholarly journals BIOFACQUIM: A Mexican Compound Database of Natural Products

Biomolecules ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 31 ◽  
Author(s):  
B. Pilón-Jiménez ◽  
Fernanda Saldívar-González ◽  
Bárbara Díaz-Eufracio ◽  
José Medina-Franco
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Physicochemical Properties ◽  
Chemical Space ◽  
Structural Diversity ◽  
Proof Of Concept ◽  
Molecular Fingerprints ◽  
The Public ◽  
Compound Database

Compound databases of natural products have a major impact on drug discovery projects and other areas of research. The number of databases in the public domain with compounds with natural origins is increasing. Several countries, Brazil, France, Panama and, recently, Vietnam, have initiatives in place to construct and maintain compound databases that are representative of their diversity. In this proof-of-concept study, we discuss the first version of BIOFACQUIM, a novel compound database with natural products isolated and characterized in Mexico. We discuss its construction, curation, and a complete chemoinformatic characterization of the content and coverage in chemical space. The profile of physicochemical properties, scaffold content, and diversity, as well as structural diversity based on molecular fingerprints is reported. BIOFACQUIM is available for free.

scholarly journals Generating Customized Compound Libraries for Drug Discovery with Machine Intelligence

2019 ◽  
Author(s):  
Michael Moret ◽  
Lukas Friedrich ◽  
Francesca Grisoni ◽  
Daniel Merk ◽  
Gisbert Schneider
Keyword(s):  
Drug Discovery ◽  
De Novo ◽  
Chemical Space ◽  
Primary Source ◽  
Structural Diversity ◽  
Machine Intelligence ◽  
Data Driven ◽  
Learning Framework ◽  
Compound Libraries ◽  
Chemical Knowledge

<div> <div> <p>Generative machine learning models sample drug-like molecules from chemical space without the need for explicit design rules. A deep learning framework for customized compound library generation is presented, aiming to enrich and expand the pharmacologically relevant chemical space with new molecular entities ‘on demand’. This de novo design approach was used to generate molecules that combine features from bioactive synthetic compounds and natural products, which are a primary source of inspiration for drug discovery. The results show that the data-driven machine intelligence acquires implicit chemical knowledge and generates novel molecules with bespoke properties and structural diversity. The method is available as an open-access tool for medicinal and bioorganic chemistry.<br></p> </div> </div>

scholarly journals Generating Customized Compound Libraries for Drug Discovery with Machine Intelligence

2019 ◽  
Author(s):  
Michael Moret ◽  
Lukas Friedrich ◽  
Francesca Grisoni ◽  
Daniel Merk ◽  
Gisbert Schneider
Keyword(s):  
Drug Discovery ◽  
De Novo ◽  
Chemical Space ◽  
Primary Source ◽  
Structural Diversity ◽  
Machine Intelligence ◽  
Data Driven ◽  
Learning Framework ◽  
Compound Libraries ◽  
Chemical Knowledge

<div> <div> <p>Generative machine learning models sample drug-like molecules from chemical space without the need for explicit design rules. A deep learning framework for customized compound library generation is presented, aiming to enrich and expand the pharmacologically relevant chemical space with new molecular entities ‘on demand’. This de novo design approach was used to generate molecules that combine features from bioactive synthetic compounds and natural products, which are a primary source of inspiration for drug discovery. The results show that the data-driven machine intelligence acquires implicit chemical knowledge and generates novel molecules with bespoke properties and structural diversity. The method is available as an open-access tool for medicinal and bioorganic chemistry.<br></p> </div> </div>

scholarly journals Structures of endothiapepsin–fragment complexes from crystallographic fragment screening using a novel, diverse and affordable 96-compound fragment library

2016 ◽  
Vol 72 (5) ◽  
pp. 346-355 ◽  
Author(s):  
Franziska U. Huschmann ◽  
Janina Linnik ◽  
Karine Sparta ◽  
Monika Ühlein ◽  
Xiaojie Wang ◽  
...  
Keyword(s):  
Amino Acids ◽  
Drug Discovery ◽  
Organic Compounds ◽  
Compound Library ◽  
Fragment Screening ◽  
Hit Rate ◽  
Screening Experiment ◽  
Fragment Library ◽  
Time Requirements ◽  
Fragment Libraries

Crystallographic screening of the binding of small organic compounds (termed fragments) to proteins is increasingly important for medicinal chemistry-oriented drug discovery. To enable such experiments in a widespread manner, an affordable 96-compound library has been assembled for fragment screening in both academia and industry. The library is selected from already existing protein–ligand structures and is characterized by a broad ligand diversity, including buffer ingredients, carbohydrates, nucleotides, amino acids, peptide-like fragments and various drug-like organic compounds. When applied to the model protease endothiapepsin in a crystallographic screening experiment, a hit rate of nearly 10% was obtained. In comparison to other fragment libraries and considering that no pre-screening was performed, this hit rate is remarkably high. This demonstrates the general suitability of the selected compounds for an initial fragment-screening campaign. The library composition, experimental considerations and time requirements for a complete crystallographic fragment-screening campaign are discussed as well as the nine fully refined obtained endothiapepsin–fragment structures. While most of the fragments bind close to the catalytic centre of endothiapepsin in poses that have been observed previously, two fragments address new sites on the protein surface. ITC measurements show that the fragments bind to endothiapepsin with millimolar affinity.

scholarly journals DrugSpaceX: a large screenable and synthetically tractable database extending drug space

2020 ◽  
Vol 49 (D1) ◽  
pp. D1170-D1178
Author(s):  
Tianbiao Yang ◽  
Zhaojun Li ◽  
Yingjia Chen ◽  
Dan Feng ◽  
Guangchao Wang ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Chemical Space ◽  
Three Dimensional ◽  
Chemical Properties ◽  
Biological Properties ◽  
Chemical Structures ◽  
Drug Molecules ◽  
Ligand Identification ◽  
Strategy Planning ◽  
Efficient Exploration

Abstract One of the most prominent topics in drug discovery is efficient exploration of the vast drug-like chemical space to find synthesizable and novel chemical structures with desired biological properties. To address this challenge, we created the DrugSpaceX (https://drugspacex.simm.ac.cn/) database based on expert-defined transformations of approved drug molecules. The current version of DrugSpaceX contains &gt;100 million transformed chemical products for virtual screening, with outstanding characteristics in terms of structural novelty, diversity and large three-dimensional chemical space coverage. To illustrate its practical application in drug discovery, we used a case study of discoidin domain receptor 1 (DDR1), a kinase target implicated in fibrosis and other diseases, to show DrugSpaceX performing a quick search of initial hit compounds. Additionally, for ligand identification and optimization purposes, DrugSpaceX also provides several subsets for download, including a 10% diversity subset, an extended drug-like subset, a drug-like subset, a lead-like subset, and a fragment-like subset. In addition to chemical properties and transformation instructions, DrugSpaceX can locate the position of transformation, which will enable medicinal chemists to easily integrate strategy planning and protection design.

scholarly journals Sulfated Non-Saccharide Glycosaminoglycan Mimetics as Novel Drug Discovery Platform for Various Pathologies

2020 ◽  
Vol 27 (21) ◽  
pp. 3412-3447 ◽  
Author(s):  
Daniel K. Afosah ◽  
Rami A. Al-Horani
Keyword(s):  
Drug Discovery ◽  
Serine Proteases ◽  
Structural Diversity ◽  
The Novel ◽  
Protein Interface ◽  
Gag Protein ◽  
Anti Cancer ◽  
Anionic Polysaccharides ◽  
Novel Drug ◽  
Biological Outcomes

Glycosaminoglycans (GAGs) are very complex, natural anionic polysaccharides. They are polymers of repeating disaccharide units of uronic acid and hexosamine residues. Owing to their template-free, spatiotemporally-controlled, and enzyme-mediated biosyntheses, GAGs possess enormous polydispersity, heterogeneity, and structural diversity which often translate into multiple biological roles. It is well documented that GAGs contribute to physiological and pathological processes by binding to proteins including serine proteases, serpins, chemokines, growth factors, and microbial proteins. Despite advances in the GAG field, the GAG-protein interface remains largely unexploited by drug discovery programs. Thus, Non-Saccharide Glycosaminoglycan Mimetics (NSGMs) have been rationally developed as a novel class of sulfated molecules that modulate GAG-protein interface to promote various biological outcomes of substantial benefit to human health. In this review, we describe the chemical, biochemical, and pharmacological aspects of recently reported NSGMs and highlight their therapeutic potentials as structurally and mechanistically novel anti-coagulants, anti-cancer agents, anti-emphysema agents, and anti-viral agents. We also describe the challenges that complicate their advancement and describe ongoing efforts to overcome these challenges with the aim of advancing the novel platform of NSGMs to clinical use.

scholarly journals BIOFACQUIM: A Mexican Compound Database of Natural Products

2018 ◽  
Author(s):  
B. Angélica Pilón-Jiménez ◽  
Fernanda I. Saldívar-González ◽  
Bárbara I. Díaz-Eufracio ◽  
José L. Medina-Franco
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Physicochemical Properties ◽  
Chemical Space ◽  
Structural Diversity ◽  
Molecular Fingerprints ◽  
Natural Origin ◽  
The Public ◽  
Compound Database

Compound databases of natural products have a major impact on drug discovery projects and other areas of research. The number of databases in the public domain with compounds from natural origin is increasing. Several countries have initiatives in place to construct and maintain compound databases that are representative of their diversity. Examples are Brazil, France, Panama and recently Vietnam. Herein, we discuss the first version of BIOFACQUIM, a novel compound database with natural products isolated and characterized in Mexico. We discuss its construction, curation, and a complete chemoinformatic characterization of the content and coverage in chemical space. It is reported the profile of physicochemical properties, scaffold content, and diversity, as well as structural diversity based on molecular fingerprints. BIOFACQUIM is freely available.

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