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Recent efforts for drug identification from phytochemicals against SARS-CoV-2: Exploration of the chemical space to identify druggable leads.

ABSTRACT: Nature, which remains a central drug discovery pool, is always looked upon to find a putative druggable lead. The natural products and phytochemical derived from plants are essential during a global health crisis. This class represents one of the most practical and promising approaches to decrease pandemic's intensity owing to their therapeutic potential. The current review is therefore kept forth to give the researchers updated information on undergoing research in allied areas of natural product-based drug discovery, particularly for Covid-19 disease. The study briefly shreds evidence from in vitro and in silico researches done so far to find a lead molecule against Covid-19. Following this, we exhaustively explored the concept of chemical space and molecular similarity parameters for the drug discovery about the lead(s) generated from in silico-based studies. The comparison was drawn using FDA approved anti-infective agents during 2015-2020 using key descriptors to evaluate druglike properties. The outcomes of results were further corroborated using Molecular Dynamics studies which suggested the outcomes in alignment with chemical space ranking. In a nutshell, current work aims to provide a holistic strategic approach to drug design, keeping in view the identified natural products derived leads for Covid-19.

SUBMITTER: Joshi G

PROVIDER: S-EPMC8018909 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Druggable chemical space and enumerative combinatorics.

Project description:BackgroundThere is a growing body of literature describing the properties of marketed drugs, the concept of drug-likeness and the vastness of chemical space. In that context, enumerative combinatorics with simple atomic components may be useful in the conception and design of structurally novel compounds for expanding and enhancing high-throughput screening (HTS) libraries.ResultsA random combination of mono- and diatomic carbon, hydrogen, nitrogen, and oxygen containing components in the absence of molecular weight constraints but with the ability to form rings affords virtual compounds that fall in bulk physicochemical space typically associated with drugs, but whose ring assemblies fall in new or under-represented areas of chemical shape space. When compared against compounds in the ChEMBL_14, MDDR, Drug Bank and Dictionary of Natural Products, the percentage of virtual compounds with a Tanimoto index of 1.0 (ECFP_4) was found to be as high as 0.21. Depending on therapeutic target, this value may be in range of what might be expected from an experimental HTS campaign in terms of a true hit rate.ConclusionVirtual compounds derived through enumerative combinatorics of simple atomic components have drug-like properties with ring assemblies that fall in new or under-represented areas of shape space. Structures derived in this manner could provide the starting point or inspiration for the design of structurally novel scaffolds in an unbiased fashion.

| S-EPMC3641967 | biostudies-literature

Pharmit: interactive exploration of chemical space.

Project description:Pharmit (http://pharmit.csb.pitt.edu) provides an online, interactive environment for the virtual screening of large compound databases using pharmacophores, molecular shape and energy minimization. Users can import, create and edit virtual screening queries in an interactive browser-based interface. Queries are specified in terms of a pharmacophore, a spatial arrangement of the essential features of an interaction, and molecular shape. Search results can be further ranked and filtered using energy minimization. In addition to a number of pre-built databases of popular compound libraries, users may submit their own compound libraries for screening. Pharmit uses state-of-the-art sub-linear algorithms to provide interactive screening of millions of compounds. Queries typically take a few seconds to a few minutes depending on their complexity. This allows users to iteratively refine their search during a single session. The easy access to large chemical datasets provided by Pharmit simplifies and accelerates structure-based drug design. Pharmit is available under a dual BSD/GPL open-source license.

| S-EPMC4987880 | biostudies-literature

Novel chemical space exploration via natural products.

Project description:Natural products (NPs) are a rich source of novel compound classes and new drugs. In the present study we have used the chemical space navigation tool ChemGPS-NP to evaluate the chemical space occupancy by NPs and bioactive medicinal chemistry compounds from the database WOMBAT. The two sets differ notably in coverage of chemical space, and tangible leadlike NPs were found to cover regions of chemical space that lack representation in WOMBAT. Property based similarity calculations were performed to identify NP neighbors of approved drugs. Several of the NPs revealed by this method were confirmed to exhibit the same activity as their drug neighbors. The identification of leads from a NP starting point may prove a useful strategy for drug discovery in the search for novel leads with unique properties.

| S-EPMC2696019 | biostudies-literature

Phytochemicals against SARS-CoV as potential drug leads.

Project description:The newly emerged SARS-CoV-2 strains from the coronavirus (CoV) family is causing one of the most disruptive pandemics of the past century. Developing antiviral drugs is a challenge for the scientific community and pharmaceutical industry. Given the health emergency, repurposing of existing antiviral, antiinflammatory or antimalarial drugs is an attractive option for controlling SARS-CoV-2 with drugs. However, phytochemicals selected based on ethnomedicinal information as well as in vitro antiviral studies could be promising as well. Here, we summarise the phytochemicals with reported anti-CoV activity, and further analyzed them computationally to accelerate validation for drug development against SARS-CoV-2. This systematic review started from the most potent phytocompounds (IC50 in μM) against SARS-CoV, followed by a cluster analysis to locate the most suitable lead(s). The advanced molecular docking used the crystallography structure of SARS-CoV-2-cysteine-like protease (SARS-CoV-2-3CLpro) as a target. In total, seventy-eight phytochemicals with anti-CoV activity against different strains in cellular assays, were selected for this computational study, and compared with two existing repurposed FDA-approved drugs: lopinavir and ritonavir. This review brings insights in the potential application of phytochemicals and their derivatives, which could guide researchers to develop safe drugs against SARS-CoV-2.

| S-EPMC7726715 | biostudies-literature

Comprehensive exploration of chemical space using trisubstituted carboranes.

Project description:A total of 42 trisubstituted carboranes categorised into five scaffolds were systematically designed and synthesized by exploiting the different reactivities of the twelve vertices of o-, m-, and p-carboranes to cover all directions in chemical space. Significant inhibitors of hypoxia inducible factor transcriptional activitay were mainly observed among scaffold V compounds (e.g., Vi-m, and Vo), whereas anti-rabies virus activity was observed among scaffold V (Va-h), scaffold II (IIb-g), and scaffold IV (IVb) compounds. The pharmacophore model predicted from compounds with scaffold V, which exhibited significant anti-rabies virus activity, agreed well with compounds IIb-g with scaffold II and compound IVb with scaffold IV. Normalized principal moment of inertia analysis indicated that carboranes with scaffolds I-V cover all regions in the chemical space. Furthermore, the first compounds shown to stimulate the proliferation of the rabies virus were found among scaffold V carboranes.

| S-EPMC8677773 | biostudies-literature

Systemic evolutionary chemical space exploration for drug discovery.

Project description:Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical entities. Compared with other screening technologies, computational de novo design has become a popular approach to overcome the limitation of current chemical libraries. Here, we reported a de novo design platform named systemic evolutionary chemical space explorer (SECSE). The platform was conceptually inspired by fragment-based drug design, that miniaturized a "lego-building" process within the pocket of a certain target. The key to virtual hits generation was then turned into a computational search problem. To enhance search and optimization, human intelligence and deep learning were integrated. Application of SECSE against phosphoglycerate dehydrogenase (PHGDH), proved its potential in finding novel and diverse small molecules that are attractive starting points for further validation. This platform is open-sourced and the code is available at http://github.com/KeenThera/SECSE.

| S-EPMC8973791 | biostudies-literature

Molpher: a software framework for systematic chemical space exploration.

Project description:BACKGROUND:Chemical space is virtual space occupied by all chemically meaningful organic compounds. It is an important concept in contemporary chemoinformatics research, and its systematic exploration is vital to the discovery of either novel drugs or new tools for chemical biology. RESULTS:In this paper, we describe Molpher, an open-source framework for the systematic exploration of chemical space. Through a process we term 'molecular morphing', Molpher produces a path of structurally-related compounds. This path is generated by the iterative application of so-called 'morphing operators' that represent simple structural changes, such as the addition or removal of an atom or a bond. Molpher incorporates an optimized parallel exploration algorithm, compound logging and a two-dimensional visualization of the exploration process. Its feature set can be easily extended by implementing additional morphing operators, chemical fingerprints, similarity measures and visualization methods. Molpher not only offers an intuitive graphical user interface, but also can be run in batch mode. This enables users to easily incorporate molecular morphing into their existing drug discovery pipelines. CONCLUSIONS:Molpher is an open-source software framework for the design of virtual chemical libraries focused on a particular mechanistic class of compounds. These libraries, represented by a morphing path and its surroundings, provide valuable starting data for future in silico and in vitro experiments. Molpher is highly extensible and can be easily incorporated into any existing computational drug design pipeline.

| S-EPMC3998053 | biostudies-literature

Exhaustive local chemical space exploration using a transformer model

Project description: Not available

| S-EPMC11345417 | biostudies-literature

A metabolomics guided exploration of marine natural product chemical space.

Project description:Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections.Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs.In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to.This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B.Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

| S-EPMC5556696 | biostudies-literature

Exploration of the chemical space and its three historical regimes.

Project description:Chemical research unveils the structure of chemical space, spanned by all chemical species, as documented in more than 200 y of scientific literature, now available in electronic databases. Very little is known, however, about the large-scale patterns of this exploration. Here we show, by analyzing millions of reactions stored in the Reaxys database, that chemists have reported new compounds in an exponential fashion from 1800 to 2015 with a stable 4.4% annual growth rate, in the long run neither affected by World Wars nor affected by the introduction of new theories. Contrary to general belief, synthesis has been the means to provide new compounds since the early 19th century, well before Wöhler's synthesis of urea. The exploration of chemical space has followed three statistically distinguishable regimes. The first one included uncertain year-to-year output of organic and inorganic compounds and ended about 1860, when structural theory gave way to a century of more regular and guided production, the organic regime. The current organometallic regime is the most regular one. Analyzing the details of the synthesis process, we found that chemists have had preferences in the selection of substrates and we identified the workings of such a selection. Regarding reaction products, the discovery of new compounds has been dominated by very few elemental compositions. We anticipate that the present work serves as a starting point for more sophisticated and detailed studies of the history of chemistry.

| S-EPMC6600933 | biostudies-literature

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