scholarly journals Bio-inspired Chemical Space Exploration of Terpenoids

2022 ◽  
Author(s):  
tao zeng ◽  
B. Andes Hess ◽  
fan zhang ◽  
ruibo wu
Keyword(s):  
Natural Products ◽  
Chemical Space ◽  
Reaction Pathway ◽  
Reaction Network ◽  
Structural Diversity ◽  
Reaction Heat ◽  
Heterologous Biosynthesis ◽  
Synthetic Accessibility ◽  
Dynamics Simulations ◽  
Intrinsic Feature

Many computational methods are used to expand the open-ended border of chemical spaces. Natural products and their derivatives are an important source for drug discovery, and some algorithms are devoted to rapidly generating pseudo-natural products, while their accessibility and chemical interpretation were often ignored or underestimated, thus hampering experimental synthesis in practice. Herein, a bio-inspired strategy (named TeroGen) is proposed, in which the cyclization and decoration stage of terpenoid biosynthesis were mimicked by meta-dynamics simulations and deep learning models respectively, to explore their chemical space. In the protocol of TeroGen, the synthetic accessibility is validated by reaction energetics (reaction barrier and reaction heat) based on the GFN2-xTB methods. Chemical interpretation is an intrinsic feature as the reaction pathway is bioinspired and triggered by the RMSD-PP method in conjunction with an encoder-decoder architecture. This is quite distinct from conventional library/fragment-based or rule-based strategies, by using TeroGen, new reaction routes are feasibly explored to increase the structural diversity. For example, only a rather limited number of sesterterpenoids in our training set is included in this work, but our TeroGen would predict more than 30000 sesterterpenoids and map out the reaction network with super efficiency, ten times as many as the known sesterterpenoids (less than 2500). In sum, TeroGen not only greatly expands the chemical space of terpenoids but also provides various plausible biosynthetic pathways, which are crucial clues for heterologous biosynthesis, bio-mimic and chemical synthesis of complicated terpenoids.

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 Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning

2020 ◽  
Author(s):  
Alice Capecchi ◽  
Jean-Louis Reymond
Keyword(s):  
Machine Learning ◽  
Natural Products ◽  
Chemical Space ◽  
Chemical Properties ◽  
Structural Diversity ◽  
Physico Chemical ◽  
Machine Learning Model ◽  
Interactive Map ◽  
Microbial Natural Products ◽  
Tree Map

<p>Microbial natural products (NPs) are an important source of drugs. However, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint suitable for molecules across very different sizes, to analyze the Natural Products Atlas (NPAtlas), a database of 25,523 NPs of bacterial or fungal origin downloaded from <a href="https://www.npatlas.org/joomla/">https://www.npatlas.org/joomla/</a>. To visualize NPAtlas by MAP4 similarity, we used the dimensionality reduction method tree map (TMAP) (<a href="http://tmap.gdb.tools/">http://tmap.gdb.tools</a>). The resulting interactive map (<a href="https://tm.gdb.tools/map4/npatlas_map_tmap/">https://tm.gdb.tools/map4/npatlas_map_tmap/</a>) organizes molecules by physico-chemical properties and compound families such as peptides, glycosides, polyphenols or terpenoids. Remarkably, the map separates bacterial and fungal NPs from one another, revealing that these two compound families are intrinsically different despite of their related biosynthetic pathways. We used these differences to train a machine learning model capable of distinguishing between NPs of bacterial or fungal origin. </p>

scholarly journals Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning

Biomolecules ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1385
Author(s):  
Alice Capecchi ◽  
Jean-Louis Reymond
Keyword(s):  
Machine Learning ◽  
Natural Products ◽  
Chemical Space ◽  
Chemical Properties ◽  
Structural Diversity ◽  
Physico Chemical ◽  
Machine Learning Model ◽  
Interactive Map ◽  
Microbial Natural Products ◽  
Tree Map

Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint suitable for molecules across very different sizes, to analyze the Natural Products Atlas (NPAtlas), a database of 25,523 NPs of bacterial or fungal origin. To visualize NPAtlas by MAP4 similarity, we used the dimensionality reduction method tree map (TMAP). The resulting interactive map organizes molecules by physico-chemical properties and compound families such as peptides and glycosides. Remarkably, the map separates bacterial and fungal NPs from one another, revealing that these two compound families are intrinsically different despite their related biosynthetic pathways. We used these differences to train a machine learning model capable of distinguishing between NPs of bacterial or fungal origin.

scholarly journals Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products

2021 ◽  
Vol 9 ◽  
Author(s):  
Kauê Santana ◽  
Lidiane Diniz do Nascimento ◽  
Anderson Lima e Lima ◽  
Vinícius Damasceno ◽  
Claudio Nahum ◽  
...  
Keyword(s):  
Natural Products ◽  
Virtual Screening ◽  
Bioactive Compounds ◽  
Chemical Space ◽  
Structural Diversity ◽  
Industrial Applications ◽  
Bioactive Molecules ◽  
Natural Sources ◽  
Compound Libraries ◽  
Pharmacokinetic Properties

Natural products are continually explored in the development of new bioactive compounds with industrial applications, attracting the attention of scientific research efforts due to their pharmacophore-like structures, pharmacokinetic properties, and unique chemical space. The systematic search for natural sources to obtain valuable molecules to develop products with commercial value and industrial purposes remains the most challenging task in bioprospecting. Virtual screening strategies have innovated the discovery of novel bioactive molecules assessing in silico large compound libraries, favoring the analysis of their chemical space, pharmacodynamics, and their pharmacokinetic properties, thus leading to the reduction of financial efforts, infrastructure, and time involved in the process of discovering new chemical entities. Herein, we discuss the computational approaches and methods developed to explore the chemo-structural diversity of natural products, focusing on the main paradigms involved in the discovery and screening of bioactive compounds from natural sources, placing particular emphasis on artificial intelligence, cheminformatics methods, and big data analyses.

scholarly journals Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning

2020 ◽  
Author(s):  
Alice Capecchi ◽  
Jean-Louis Reymond
Keyword(s):  
Machine Learning ◽  
Natural Products ◽  
Chemical Space ◽  
Chemical Properties ◽  
Structural Diversity ◽  
Physico Chemical ◽  
Machine Learning Model ◽  
Interactive Map ◽  
Microbial Natural Products ◽  
Tree Map

<p>Microbial natural products (NPs) are an important source of drugs. However, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint suitable for molecules across very different sizes, to analyze the Natural Products Atlas (NPAtlas), a database of 25,523 NPs of bacterial or fungal origin downloaded from <a href="https://www.npatlas.org/joomla/">https://www.npatlas.org/joomla/</a>. To visualize NPAtlas by MAP4 similarity, we used the dimensionality reduction method tree map (TMAP) (<a href="http://tmap.gdb.tools/">http://tmap.gdb.tools</a>). The resulting interactive map (<a href="https://tm.gdb.tools/map4/npatlas_map_tmap/">https://tm.gdb.tools/map4/npatlas_map_tmap/</a>) organizes molecules by physico-chemical properties and compound families such as peptides, glycosides, polyphenols or terpenoids. Remarkably, the map separates bacterial and fungal NPs from one another, revealing that these two compound families are intrinsically different despite of their related biosynthetic pathways. We used these differences to train a machine learning model capable of distinguishing between NPs of bacterial or fungal origin. </p>

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.

Metal-, and Organocatalyst-Free One-Pot Assembly of Chiral Aza-Tricyclic Molecules: Creating Six Contiguous Stereocenters from 2-D-Structures and an Amino Acid

2020 ◽  
Author(s):  
Dung Do
Keyword(s):  
Amino Acid ◽  
Chemical Space ◽  
Structural Diversity ◽  
Therapeutic Agents ◽  
Chiral Molecules ◽  
One Pot ◽  
Complex Molecules ◽  
Chiral Catalyst ◽  
Chiral Complex ◽  
Free Process

<p>Chiral molecules with their defined 3-D structures are of paramount importance for the study of chemical biology and drug discovery. Having rich structural diversity and unique stereoisomerism, chiral molecules offer a large chemical space that can be explored for the design of new therapeutic agents.<sup>1</sup> Practically, chiral architectures are usually prepared from organometallic and organocatalytic processes where a transition metal or an organocatalyst is tailor-made for desired reactions. As a result, developing a method that enables rapid assembly of chiral complex molecules under metal- and organocatalyst-free condition represents a daunting challenge. Here we developed a straightforward route to create a chiral 3-D structure from 2-D structures and an amino acid without any chiral catalyst. The center of this research is the design of a <a>special chiral spiroimidazolidinone cyclohexadienone intermediate</a>, a merger of a chiral reactive substrate with multiple nucleophillic/electrophillic sites and a transient organocatalyst. <a>This unique substrate-catalyst (“subcatalyst”) dual role of the intermediate enhances </a><a>the coordinational proximity of the chiral substrate and catalyst</a> in the key Aza-Michael/Michael cascade resulting in a substantial steric discrimination and an excellent overall diastereoselectivity. Whereas the “subcatalyst” (hidden catalyst) is not present in the reaction’s initial components, which renders a chiral catalyst-free process, it is strategically produced to promote sequential self-catalyzed reactions. The success of this methodology will pave the way for many efficient preparations of chiral complex molecules and aid for the quest to create next generation of therapeutic agents.</p>

A Paramedic Treatment for Modeling Explicitly Solvated Chemical Reaction Mechanisms

2018 ◽  
Author(s):  
Yasemin Basdogan ◽  
John Keith
Keyword(s):  
Reaction Mechanism ◽  
Chemical Reaction ◽  
Reaction Mechanisms ◽  
Reaction Pathway ◽  
Optimization Procedure ◽  
Cost Effective ◽  
Chemical Reaction Mechanisms ◽  
Solvent Molecules ◽  
Dynamics Simulations ◽  
Mbh Reaction

<div> <div> <div> <p>We report a static quantum chemistry modeling treatment to study how solvent molecules affect chemical reaction mechanisms without dynamics simulations. This modeling scheme uses a global optimization procedure to identify low energy intermediate states with different numbers of explicit solvent molecules and then the growing string method to locate sequential transition states along a reaction pathway. Testing this approach on the acid-catalyzed Morita-Baylis-Hillman (MBH) reaction in methanol, we found a reaction mechanism that is consistent with both recent experiments and computationally intensive dynamics simulations with explicit solvation. In doing so, we explain unphysical pitfalls that obfuscate computational modeling that uses microsolvated reaction intermediates. This new paramedic approach can promisingly capture essential physical chemistry of the complicated and multistep MBH reaction mechanism, and the energy profiles found with this model appear reasonably insensitive to the level of theory used for energy calculations. Thus, it should be a useful and computationally cost-effective approach for modeling solvent mediated reaction mechanisms when dynamics simulations are not possible. </p> </div> </div> </div>

scholarly journals Chemical Elicitors Induce Rare Bioactive Secondary Metabolites in Deep-Sea Bacteria under Laboratory Conditions

Metabolites ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 107
Author(s):  
Rafael de Felício ◽  
Patricia Ballone ◽  
Cristina Freitas Bazzano ◽  
Luiz F. G. Alves ◽  
Renata Sigrist ◽  
...  
Keyword(s):  
Natural Products ◽  
Secondary Metabolites ◽  
Natural Product ◽  
Deep Sea ◽  
Chemical Space ◽  
Bacterial Genome ◽  
Vast Number ◽  
Bacterial Metabolites ◽  
Laboratory Conditions ◽  
Deep Sea Bacteria

Bacterial genome sequencing has revealed a vast number of novel biosynthetic gene clusters (BGC) with potential to produce bioactive natural products. However, the biosynthesis of secondary metabolites by bacteria is often silenced under laboratory conditions, limiting the controlled expression of natural products. Here we describe an integrated methodology for the construction and screening of an elicited and pre-fractionated library of marine bacteria. In this pilot study, chemical elicitors were evaluated to mimic the natural environment and to induce the expression of cryptic BGCs in deep-sea bacteria. By integrating high-resolution untargeted metabolomics with cheminformatics analyses, it was possible to visualize, mine, identify and map the chemical and biological space of the elicited bacterial metabolites. The results show that elicited bacterial metabolites correspond to ~45% of the compounds produced under laboratory conditions. In addition, the elicited chemical space is novel (~70% of the elicited compounds) or concentrated in the chemical space of drugs. Fractionation of the crude extracts further evidenced minor compounds (~90% of the collection) and the detection of biological activity. This pilot work pinpoints strategies for constructing and evaluating chemically diverse bacterial natural product libraries towards the identification of novel bacterial metabolites in natural product-based drug discovery pipelines.

Enzymatic dimerization in the biosynthetic pathway of microbial natural products

2021 ◽  
Author(s):  
Jiawang Liu ◽  
Anan Liu ◽  
Youcai Hu
Keyword(s):  
Natural Products ◽  
Biosynthetic Pathway ◽  
Structural Diversity ◽  
Cytochrome P450s ◽  
Microbial Natural Products

Cytochrome P450s, laccases, and intermolecular [4 + 2] cyclases, along with other enzymes were utilized to catalyze varied dimerization of matured natural products so as to create the structural diversity and complexity in microorganisms.

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