scholarly journals Generative AI Design and Exploration of Nucleoside Analogs

2021 ◽  
Author(s):  
Damien Dablain ◽  
Geoffrey Siwo ◽  
Nitesh Chawla
Keyword(s):  
Drug Discovery ◽  
Prebiotic Chemistry ◽  
Antiviral Drug ◽  
Nucleoside Analogs ◽  
Building Blocks ◽  
Generative Models ◽  
Chemical Transformations ◽  
Generative Design ◽  
Wide Range

Nucleosides are fundamental building blocks of DNA and RNA in all life forms and viruses. In addition, natural nucleosides and their analogs are critical in prebiotic chemistry, innate immunity, signaling, antiviral drug discovery and artificial synthesis of DNA / RNA sequences. Combined with the fact that quantitative structure activity relationships (QSAR) have been widely performed to understand their antiviral activity, nucleoside analogs could be used to benchmark generative molecular design. Here, we undertake the first generative design of nucleoside analogs using an approach that we refer to as the Conditional Randomized Transformer (CRT). We also benchmark our model against five previously published molecular generative models. We demonstrate that AI-generated molecules include nucleoside analogs that are of significance in a wide range of areas including prebiotic chemistry, antiviral drug discovery and synthesis of oligonucleotides. Our results show that CRT explores distinct molecular spaces and chemical transformations, some of which are similar to those undertaken by nature and medicinal chemists. Finally, we demonstrate the potential application of the CRT model in the generative design of molecules conditioned on Remdesivir and Molnupiravir as well as other nucleoside analogs with in vitro activity against SARS-CoV-2. One-Sentence Summary: Generative design of nucleoside analogs relevant to antiviral drug discovery, prebiotic chemistry and synthetic biology.

Synthesis of sp3-Enriched β-Fluoro Sulfonyl Chlorides

Synthesis ◽  
2020 ◽  
Author(s):  
Oleksandr O. Grygorenko ◽  
Rustam Gurbanov ◽  
Andriy Sokolov ◽  
Sergey Golovach ◽  
Kostiantyn Melnykov ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Double Bond ◽  
Building Blocks ◽  
Protecting Groups ◽  
Sulfonyl Chlorides ◽  
Wide Range ◽  
Cyclic Compounds

AbstractA three-step approach to the synthesis of sp3-enriched β-fluoro sulfonyl chlorides starting from alkenes is reported. The method was successfully applied to a wide range of acyclic and cyclic substrates, bearing either an exocyclic or an endocyclic double bond. The procedure worked with a wide range of substrates and tolerated a number of functional and protecting groups. Moreover, the target cyclic compounds were obtained as single cis diastereomers on a multigram scale. The title compounds are promising building blocks for drug discovery that can be used to obtain sp3-enriched β-fluoro and α,β-unsaturated sulfonamides.

scholarly journals De novo design of self-assembling helical protein filaments

Science ◽  
2018 ◽  
Vol 362 (6415) ◽  
pp. 705-709 ◽  
Author(s):  
Hao Shen ◽  
Jorge A. Fallas ◽  
Eric Lynch ◽  
William Sheffler ◽  
Bradley Parry ◽  
...  
Keyword(s):  
De Novo ◽  
Computational Design ◽  
Building Blocks ◽  
Repeat Units ◽  
Self Assembling ◽  
Wide Range ◽  
Helical Protein ◽  
Monomeric Proteins

We describe a general computational approach to designing self-assembling helical filaments from monomeric proteins and use this approach to design proteins that assemble into micrometer-scale filaments with a wide range of geometries in vivo and in vitro. Cryo–electron microscopy structures of six designs are close to the computational design models. The filament building blocks are idealized repeat proteins, and thus the diameter of the filaments can be systematically tuned by varying the number of repeat units. The assembly and disassembly of the filaments can be controlled by engineered anchor and capping units built from monomers lacking one of the interaction surfaces. The ability to generate dynamic, highly ordered structures that span micrometers from protein monomers opens up possibilities for the fabrication of new multiscale metamaterials.

scholarly journals Aptamers in the Treatment of Bacterial Infections: Problems and Prospects

2016 ◽  
Vol 71 (5) ◽  
pp. 350-358
Author(s):  
N. A. Zeninskaya ◽  
A. V. Kolesnikov ◽  
A. K. Ryabko ◽  
I. G. Shemyakin ◽  
I. A. Dyatlov ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput Screening ◽  
Bacterial Infections ◽  
Point Of View ◽  
Aptamer Selection ◽  
Wide Range ◽  
Therapeutic Molecules ◽  
Molecular Selection ◽  
The Stability

Aptamers are short single-stranded oligonucleotides which are selected via targeted chemical evolution in vitro to bind a molecular target of interest. The aptamer selection technology is designated as SELEX (Systematic evolution of ligands by exponential enrichment). SELEX enables isolation of oligonucleotide aptamers binding a wide range of targets of interest with little respect for their nature and molecular weight. A number of applications of aptamer selection were developed ranging from biosensor technologies to antitumor drug discovery. First aptamer-based pharmaceutical (Macugen) was approved by FDA for clinical use in 2004, and since then more than ten aptamer-based drugs undergo various phases of clinical trials. From the medicinal chemist’s point of view, aptamers represent a new class of molecules suitable for the development of new therapeutics. Due to the stability, relative synthesis simplicity, and development of advanced strategies of target specific molecular selection, aptamers attract increased attention of drug discovery community. Difficulties of the development of next-generation antibiotics basing on the conventional basis of combinatorial chemistry and high-throughput screening have also amplified the interest to aptamer-based therapeutic candidates. The present article reviews the investigations focused on the development of antibacterial aptamers and discusses the potential and current limitations of the use of this type of therapeutic molecules.

scholarly journals Déjà vu: Stimulating Open Drug Discovery for SARS-CoV-2

2020 ◽  
Author(s):  
Sean Ekins ◽  
Melina Mottin ◽  
Paulo R. P. S. Ramos ◽  
Bruna K. P. Sousa ◽  
Bruno Junior Neves ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Ebola Virus ◽  
Antiviral Drug ◽  
Open Science ◽  
Virus Rna ◽  
Deja Vu ◽  
Déjà Vu ◽  
Approved Drugs

In the past decade we have seen two major Ebola virus outbreaks in Africa, the Zika virus in Brazil and the current outbreak of coronavirus disease which has been named "severe acute respiratory syndrome coronavirus 2" (SARS-CoV-2). There is a strong sense of Déjà vu as the world is caught flat footed without effective treatments to administer to patients. Our team has been actively involved in several small molecule drug discovery efforts for the preceding virus outbreaks. In 2014 we used machine learning to identify 3 new molecules to test for the Ebola virus and these were subsequently shown to be active in vitro and in vivo. We have also been involved in open science approaches that leverage the community to help. In 2016 we launched the OpenZika project as an IBM World Community Grid Project that used distributed computing power of volunteers to dock large numbers of compounds into Zika and related flavivirus targets. This led us into several collaborations in which we validated computational predictions in vitro. With both of these initiatives there was some knowledge of the virus, many compounds had already been tested in the case of Ebola, whereas for Zika initially all we had was the virus RNA sequence. In the current SARS-CoV-2 outbreak, this was a completely new virus and the scientists in China and elsewhere have started from scratch. In the space of a few weeks since the outbreak is acknowledged to have started, there are now compounds suggested as active in vitro and molecules repurposed in clinical trials. While this has been impressive, we propose there may still be gaps in our approach to drug discovery for such outbreaks. There is an opportunity to repurpose additional approved drugs for this virus and we now suggest how these might be identified leveraging prior work on MERS-CoV, SARS-CoV and other viruses. We also describe some of the immense challenges and limitations of the open antiviral drug discovery approaches we have been involved in.

scholarly journals A Review of the Ethnomedicinal Uses, Biological Activities, and Triterpenoids of Euphorbia Species

Molecules ◽  
2020 ◽  
Vol 25 (17) ◽  
pp. 4019
Author(s):  
Douglas Kemboi ◽  
Xolani Peter ◽  
Moses Langat ◽  
Jacqueline Tembu
Keyword(s):  
Drug Discovery ◽  
Biological Activities ◽  
Chemical Constituents ◽  
Structural Diversity ◽  
Pharmacological Properties ◽  
Anticancer Activities ◽  
Sensory Disorders ◽  
Wide Range ◽  
Ethnomedicinal Uses

The genus Euphorbia is one of the largest genera in the spurge family, with diversity in range, distribution, and morphology. The plant species in this genus are widely used in traditional medicine for the treatment of diseases, ranging from respirational infections, body and skin irritations, digestion complaints, inflammatory infections, body pain, microbial illness, snake or scorpion bites, pregnancy, as well as sensory disorders. Their successes have been attributed to the presence of diverse phytochemicals like polycyclic and macrocyclic diterpenes with various pharmacological properties. As a result, Euphorbia diterpenes are of interest to chemists and biochemists with regard to drug discovery from natural products due to their diverse therapeutic applications as well as their great structural diversity. Other chemical constituents such as triterpenoids have also been reported to possess various pharmacological properties, thus supporting the traditional uses of the Euphorbia species. These triterpenoids can provide potential leads that can be developed into pharmaceutical compounds for a wide range of medicinal applications. However, there are scattered scientific reports about the anticancer activities of these constituents. Harnessing such information could provide a database of bioactive pharmacopeia or targeted scaffolds for drug discovery. Therefore, this review presents an updated and comprehensive summary of the ethnomedicinal uses, phytochemistry, and the anticancer activities of the triterpenoids of Euphorbia species. Most of the reported triterpenoids in this review belong to tirucallane, cycloartanes, lupane, oleanane, ursane, and taraxane subclass. Their anticancer activities varied distinctly with the majority of them exhibiting significant cytotoxic and anticancer activities in vitro. It is, therefore, envisaged that the report on Euphorbia triterpenoids with interesting anticancer activities will form a database of potential leads or scaffolds that could be advanced into the clinical trials with regard to drug discovery.

scholarly journals The complex structure of GRL0617 and SARS-CoV-2 PLpro reveals a hot spot for antiviral drug discovery

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ziyang Fu ◽  
Bin Huang ◽  
Jinle Tang ◽  
Shuyan Liu ◽  
Ming Liu ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Hot Spot ◽  
Dominant Role ◽  
Complex Structure ◽  
Antiviral Drug ◽  
Binding Pocket ◽  
Virus Maturation ◽  
C Terminus ◽  
Approved Drugs

AbstractSARS-CoV-2 is the pathogen responsible for the COVID-19 pandemic. The SARS-CoV-2 papain-like cysteine protease (PLpro) has been implicated in playing important roles in virus maturation, dysregulation of host inflammation, and antiviral immune responses. The multiple functions of PLpro render it a promising drug target. Therefore, we screened a library of approved drugs and also examined available inhibitors against PLpro. Inhibitor GRL0617 showed a promising in vitro IC50 of 2.1 μM and an effective antiviral inhibition in cell-based assays. The co-crystal structure of SARS-CoV-2 PLproC111S in complex with GRL0617 indicates that GRL0617 is a non-covalent inhibitor and it resides in the ubiquitin-specific proteases (USP) domain of PLpro. NMR data indicate that GRL0617 blocks the binding of ISG15 C-terminus to PLpro. Using truncated ISG15 mutants, we show that the C-terminus of ISG15 plays a dominant role in binding PLpro. Structural analysis reveals that the ISG15 C-terminus binding pocket in PLpro contributes a disproportionately large portion of binding energy, thus this pocket is a hot spot for antiviral drug discovery targeting PLpro.

scholarly journals Deep Generative Models for Ligand-based de Novo Design Applied to Multi-parametric Optimization

2021 ◽  
Author(s):  
Quentin Perron ◽  
Olivier Mirguet ◽  
Hamza Tajmouati ◽  
Adam Skiredj ◽  
Anne Rojas ◽  
...  
Keyword(s):  
Deep Learning ◽  
Drug Discovery ◽  
De Novo ◽  
Molecular Design ◽  
Chemical Space ◽  
New Technology ◽  
De Novo Design ◽  
Generative Models ◽  
De Novo Molecular Design

<div> <div> <div> <p>Multi-Parameter Optimization (MPO) is a major challenge in New Chemical Entity (NCE) drug discovery projects, and the inability to identify molecules meeting all the criteria of lead optimization (LO) is an important cause of NCE project failure. Several ligand- and structure-based de novo design methods have been published over the past decades, some of which have proved useful multiobjective optimization. However, there is still need for improvement to better address the chemical feasibility of generated compounds as well as increasing the explored chemical space while tackling the MPO challenge. Recently, promising results have been reported for deep learning generative models applied to de novo molecular design, but until now, to our knowledge, no report has been made of the value of this new technology for addressing MPO in an actual drug discovery project. Our objective in this study was to evaluate the potential of a ligand-based de novo design technology using deep learning generative models to accelerate the discovery of an optimized lead compound meeting all in vitro late stage LO criteria. </p> </div> </div> </div>

scholarly journals Deep Generative Models for Ligand-based de Novo Design Applied to Multi-parametric Optimization

2021 ◽  
Author(s):  
Quentin Perron ◽  
Olivier Mirguet ◽  
Hamza Tajmouati ◽  
Adam Skiredj ◽  
Anne Rojas ◽  
...  
Keyword(s):  
Deep Learning ◽  
Drug Discovery ◽  
De Novo ◽  
Molecular Design ◽  
Chemical Space ◽  
New Technology ◽  
De Novo Design ◽  
Generative Models ◽  
De Novo Molecular Design

<div> <div> <div> <p>Multi-Parameter Optimization (MPO) is a major challenge in New Chemical Entity (NCE) drug discovery projects, and the inability to identify molecules meeting all the criteria of lead optimization (LO) is an important cause of NCE project failure. Several ligand- and structure-based de novo design methods have been published over the past decades, some of which have proved useful multiobjective optimization. However, there is still need for improvement to better address the chemical feasibility of generated compounds as well as increasing the explored chemical space while tackling the MPO challenge. Recently, promising results have been reported for deep learning generative models applied to de novo molecular design, but until now, to our knowledge, no report has been made of the value of this new technology for addressing MPO in an actual drug discovery project. Our objective in this study was to evaluate the potential of a ligand-based de novo design technology using deep learning generative models to accelerate the discovery of an optimized lead compound meeting all in vitro late stage LO criteria. </p> </div> </div> </div>

scholarly journals Euphorbia Diterpenes: An Update of Isolation, Structure, Pharmacological Activities and Structure–Activity Relationship

Molecules ◽  
2021 ◽  
Vol 26 (16) ◽  
pp. 5055
Author(s):  
Douglas Kemboi ◽  
Xavier Siwe-Noundou ◽  
Rui W. M. Krause ◽  
Moses K. Langat ◽  
Vuyelwa Jacqueline Tembu
Keyword(s):  
Drug Discovery ◽  
Structural Diversity ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Hydroxyl Group ◽  
Pharmacological Activities ◽  
Structure Activity ◽  
Wide Range ◽  
Ic50 Values

Euphorbia species have a rich history of ethnomedicinal use and ethnopharmacological applications in drug discovery. This is due to the presence of a wide range of diterpenes exhibiting great structural diversity and pharmacological activities. As a result, Euphorbia diterpenes have remained the focus of drug discovery investigations from natural products. The current review documents over 350 diterpenes, isolated from Euphorbia species, their structures, classification, biosynthetic pathways, and their structure–activity relationships for the period covering 2013–2020. Among the isolated diterpenes, over 20 skeletal structures were identified. Lathyrane, jatrophane, ingenane, ingenol, and ingol were identified as the major diterpenes in most Euphorbia species. Most of the isolated diterpenes were evaluated for their cytotoxicity activities, multidrug resistance abilities, and inhibitory activities in vitro, and reported good activities with significant half-inhibitory concentration (IC50) values ranging from 10–50 µM. The lathyranes, isopimaranes, and jatrophanes diterpenes were further found to show potent inhibition of P-glycoprotein, which is known to confer drug resistance abilities in cells leading to decreased cytotoxic effects. Structure–activity relationship (SAR) studies revealed the significance of a free hydroxyl group at position C-3 in enhancing the anticancer and anti-inflammatory activities and the negative effect it has in position C-2. Esterification of this functionality, in selected diterpenes, was found to enhance these activities. Thus, Euphorbia diterpenes offer a valuable source of lead compounds that could be investigated further as potential candidates for drug discovery.

scholarly journals Early Drug Discovery and Development of Novel Cancer Therapeutics Targeting DNA Polymerase Eta (POLH)

2021 ◽  
Vol 11 ◽  
Author(s):  
David M. Wilson ◽  
Matthew A. J. Duncton ◽  
Caleb Chang ◽  
Christine Lee Luo ◽  
Taxiarchis M. Georgiadis ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Dna Polymerase ◽  
Synthetic Lethality ◽  
Cancer Therapeutics ◽  
Nucleoside Analogs ◽  
Standard Of Care ◽  
Rapid Identification ◽  
Cancer Therapies ◽  
Polymerase Eta

Polymerase eta (or Pol η or POLH) is a specialized DNA polymerase that is able to bypass certain blocking lesions, such as those generated by ultraviolet radiation (UVR) or cisplatin, and is deployed to replication foci for translesion synthesis as part of the DNA damage response (DDR). Inherited defects in the gene encoding POLH (a.k.a., XPV) are associated with the rare, sun-sensitive, cancer-prone disorder, xeroderma pigmentosum, owing to the enzyme’s ability to accurately bypass UVR-induced thymine dimers. In standard-of-care cancer therapies involving platinum-based clinical agents, e.g., cisplatin or oxaliplatin, POLH can bypass platinum-DNA adducts, negating benefits of the treatment and enabling drug resistance. POLH inhibition can sensitize cells to platinum-based chemotherapies, and the polymerase has also been implicated in resistance to nucleoside analogs, such as gemcitabine. POLH overexpression has been linked to the development of chemoresistance in several cancers, including lung, ovarian, and bladder. Co-inhibition of POLH and the ATR serine/threonine kinase, another DDR protein, causes synthetic lethality in a range of cancers, reinforcing that POLH is an emerging target for the development of novel oncology therapeutics. Using a fragment-based drug discovery approach in combination with an optimized crystallization screen, we have solved the first X-ray crystal structures of small novel drug-like compounds, i.e., fragments, bound to POLH, as starting points for the design of POLH inhibitors. The intrinsic molecular resolution afforded by the method can be quickly exploited in fragment growth and elaboration as well as analog scoping and scaffold hopping using medicinal and computational chemistry to advance hits to lead. An initial small round of medicinal chemistry has resulted in inhibitors with a range of functional activity in an in vitro biochemical assay, leading to the rapid identification of an inhibitor to advance to subsequent rounds of chemistry to generate a lead compound. Importantly, our chemical matter is different from the traditional nucleoside analog-based approaches for targeting DNA polymerases.

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