Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 195
Filter
1.
Trends Pharmacol Sci ; 2022.
Article in English | PubMed | ID: covidwho-2036566

ABSTRACT

While vaccines remain at the forefront of global healthcare responses, pioneering therapeutics against SARS-CoV-2 are expected to fill the gaps for waning immunity. Rapid development and approval of orally available direct-acting antivirals targeting crucial SARS-CoV-2 proteins marked the beginning of the era of small-molecule drugs for COVID-19. In that regard, the papain-like protease (PLpro) can be considered a major SARS-CoV-2 therapeutic target due to its dual biological role in suppressing host innate immune responses and in ensuring viral replication. Here, we summarize the challenges of targeting PLpro and innovative early-stage PLpro-specific small molecules. We propose that state-of-the-art computer-aided drug design (CADD) methodologies will play a critical role in the discovery of PLpro compounds as a novel class of COVID-19 drugs.

2.
Computer Aided Drug Design (CADD): From Ligand-Based Methods to Structure-Based Approaches ; : 17-55, 2022.
Article in English | Scopus | ID: covidwho-2027799

ABSTRACT

The drug discovery paradigm has been very time-consuming, challenging, and expensive;however, the disease conditions originating from bacteria, virus, protozoa, fungus and other microorganisms are steadily shooting up. For instance, COVID-19 is the latest viral infection that affects millions of people and the world’s economy very severely. Therefore, the quest for discovery of novel and potent drug compounds against deadly pathogens is crucial at the moment. Despite a lot of drawbacks in drug discovery and development and its pertaining technology, the advancement must be taken into account so the time duration and cost would be minimized. In this chapter, basic principles in drug design and discovery have been discussed together with advances in drug development. © 2022 Elsevier Inc. All rights reserved.

3.
Computational and Structural Biotechnology Journal ; 2022.
Article in English | ScienceDirect | ID: covidwho-2007642

ABSTRACT

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has led to a global pandemic. Deep learning (DL) technology and molecular dynamics (MD) simulation are two mainstream computational approaches to investigate the geometric, chemical and structural features of protein and guide the relevant drug design. Despite a large amount of research papers focusing on drug design for SARS-COV-2 using DL architectures, it remains unclear how the binding energy of the protein-protein/ligand complex dynamically evolves which is also vital for drug development. In addition, traditional deep neural networks usually have obvious deficiencies in predicting the interaction sites as protein conformation changes. In this review, we introduce the latest progresses of the DL and DL-based MD simulation approaches in structure-based drug design (SBDD) for SARS-CoV-2 which could address the problems of protein structure and binding prediction, drug virtual screening, molecular docking and complex evolution. Furthermore, the current challenges and future directions of DL-based MD simulation for SBDD are also discussed.

4.
Trends in Pharmacological Sciences ; 2022.
Article in English | ScienceDirect | ID: covidwho-1996588

ABSTRACT

While vaccines remain at the forefront of global healthcare responses, pioneering therapeutics against SARS-CoV-2 are expected to fill the gaps for waning immunity. Rapid development and approval of orally-available direct-acting antivirals targeting crucial SARS-CoV-2 proteins, marked the beginning of the era of small molecule drugs for COVID-19. In that regards, the papain-like protease (PLpro) can be considered a major SARS-CoV-2 therapeutic target due to its dual biological role in suppressing host innate immune responses and in ensuring viral replication. Here, we summarise the challenges of targeting PLpro and innovative early-stage PLpro-specific small molecules. We propose that state-of-the-art computer-aided drug design (CADD) methodologies will play a critical role in the discovery of PLpro compounds as a novel class of COVID-19 drugs.

5.
Recent Pat Biotechnol ; 2022 Aug 02.
Article in English | MEDLINE | ID: covidwho-1987308

ABSTRACT

Drug discovery and development are critical processes that enable the treatment of a wide variety of health-related problems. These are time-consuming, tedious, complicated, and costly processes. Numerous difficulties arise throughout the entire process of drug discovery, from design to testing. Corona Virus Disease 2019 (COVID-19) recently posed a significant threat to global public health. SARS-Cov-2 and its variants are rapidly spreading in humans due to their high transmission rate. To effectively treat COVID-19, potential drugs and vaccines must be developed quickly. The advancement of artificial intelligence has shifted the focus of drug development away from traditional methods and toward bioinformatics tools. Computer-aided drug design techniques have demonstrated tremendous utility in dealing with massive amounts of biological data and developing efficient algorithms. Artificial intelligence enables more effective approaches to complex problems associated with drug discovery and development through the use of machine learning. Artificial intelligence-based technologies improve the pharmaceutical industry's ability to discover effective drugs. This review summarizes significant challenges encountered during the drug discovery and development processes, as well as the applications of artificial intelligence-based methods to overcome those obstacles in order to provide effective solutions to health problems. This may provide additional insight into the mechanism of action, resulting in the development of vaccines and potent substitutes for repurposed drugs that can be used to treat not only COVID-19 but also other ailments.

6.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-342220

ABSTRACT

We report for the first time the use of experimental electron density (ED) as training data for the generation of drug-like three-dimensional molecules based on the structure of a target protein pocket. Similar to a structural biologist building molecules based on their ED, our model functions with two main components: a generative adversarial network (GAN) to generate the ligand ED in the input pocket and an ED interpretation module for molecule generation. The model was tested on three targets including kinase (HPK1), protease (Covid19-3CL), and nuclear receptor (VDR), and evaluated with a reference dataset composed of over 8,000 compounds that have their activities reported in the literature. The evaluation examined the chemical validity, chemical space distribution-based diversity, and similarity with reference active compounds concerning the molecular structure and pocket-binding mode. Our model can reproduce classical active compounds and can also generate novel molecules with similar binding modes as active compounds, making it a promising tool for library generation supporting high-throughput virtual screening. Our model is available as an online service to academic users via https://edmg.stonewise.cn/#/create.

7.
chemRxiv; 2022.
Preprint in English | ChemRxiv | ID: ppcovidwho-341888

ABSTRACT

The search for efficient inhibitors of the SARS-CoV-2 enzymes remains important due to the continuing COVID-19 pandemic. We report the results of computational modeling of the reactions of the SARS-CoV-2 main protease (MPro) with four potential covalent inhibitors. Two of them, carmofur and nirmatrelvir, have been shown experimentally the ability to inhibit MPro. Two other compounds, X77A and X77C, were designed computationally in this work, derived from the structure of X77, a non-covalent inhibitor forming a tight surface complex with MPro. We modified the X77 structure by introducing warheads capable of efficient chemical reactions with the catalytic cysteine residue in the MPro active site. The reactions of the four molecules with MPro were investigated by quantum mechanics/molecular mechanics (QM/MM) calculations. According to calculations, the reactions for all four compounds are exothermic, with sufficiently low barriers, suggesting efficient inhibition of the enzyme. From the chemical perspective, the four compounds react with MPro following three distinct mechanisms. In all cases, the reaction is initiated by a nucleophilic attack of the thiolate group of the deprotonated cysteine residue from the catalytic dyad Cys145-His41 of MPro. In the case of carmofur and X77A, the covalent binding of the thiolate to the ligand involves the formation of the fluoro-uracil leaving group. The reaction with X77C follows the nucleophilic aromatic substitution SNAr mechanism. The reaction of MPro with nirmatrelvir, which has a reactive nitrile group, leads to the formation of the covalent thioimidate adduct with the thiolate of the Cys145 residue in the enzyme active site.

8.
Pharma Times ; 54(4-5):17-22, 2022.
Article in English | EMBASE | ID: covidwho-1980810

ABSTRACT

The advancement of Artificial intelligence (AI) is found to have dual appearances as it can create the betterment of society and can threaten employment. AI is the automating process which has led to innovation in various educational methods as well as automated business procedures. Major disease areas that use AI tools include cancer, neurology and cardiology. The emergent idea of adopting AI in the drug development process has shifted from hype to hope. AI chains the decision-making processes for prevailing drugs & expanded treatments for other conditions, as well as accelerates the clinical trials procedure by finding the right patients from a number of data sources. Integrating AI into the healthcare ecosystem allows for a multitude of benefits, including automating tasks and analysing big patient data sets to deliver better healthcare faster, and at a lower cost. Machine learning, deep learning and Artificial Intelligence can be utilised to revolutionise the drug development process. At present, the main concern of the Pharmaceutical industry is drug development programmes because of increased R&D costs and reduced efficiency. In this review, we will discuss the applications and role of AI and the possible ways it can advance the effectiveness of the drug development process.

9.
FEBS Open Bio ; 12:287, 2022.
Article in English | EMBASE | ID: covidwho-1976659

ABSTRACT

The global pandemic prompted by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has already caused more than 6 million deaths worldwide, calling for urgent effective therapeutic measures. A deep understanding of the mechanisms involved in viral replication is required. Among the nonstructural proteins (nsps) encoded by SARS-CoV-2 genome, there is the nsp14 ribonuclease, the main object of study in this work. Ribonucleases are key factors in the control of all biological processes, ensuring maturation, degradation, and quality control of all types of RNAs. Nsp14 is a bifunctional protein, holding a 3'- 5' exoribonucleolytic activity (ExoN) in the N-terminal domain, stimulated through the interaction with nsp10, and a C-terminal N7-methyltransferase activity (MTase). Both are critical for the coronavirus life cycle. In this work, we provide a complete biochemical characterization of SARS-CoV-2 nsp14-nsp10, addressing several aspects of the complex for the first time. Moreover, using a homology model, we have identified residues involved in the nsp14-nsp10 interaction that were extensively studied. We have confirmed the SARS-CoV-2 nsp14 dual function and we have shown that both ExoN and MTase activities are functionally independent. We demonstrate that the nsp14 MTase activity is independent of nsp10, contrarily to nsp14 ExoN that is upregulated in the presence of the cofactor. Additionally, our results show that the ExoN motif I has a prominent role on the ribonucleolytic activity of SARS-CoV-2 nsp14, contrasting to what was previously observed in other coronaviruses, which can be related to the pathogenesis of SARS-CoV-2. The knowledge provided in this work can serve as a basis to design effective drugs that target the pinpointed residues in order to disturb the complex assembly and affect the viral replication, ultimately, treating COVID-19 and other CoV infections.

10.
FEBS Open Bio ; 12:265, 2022.
Article in English | EMBASE | ID: covidwho-1976645

ABSTRACT

SARS-CoV-2 main protease (SARS-CoV-2 Mpro) is a cysteine protease that hydrolyses the viral polyproteins at several sites with a preference for the Leu-Gln(Ser, Ala, Gly) sequences1. The enzyme represents one of the main drug-target candidates for covid-19 syndrome because the large and deep pocket at the active site and its crucial activity for viral replication2-5 Here, we provide X-ray structural data on SARS-CoV-2 Mpro in complex with the isolated Zn2+ ion. The comparison with the apo SARSCoV- 2 Mpro shows that residues involved in zinc binding are not affected by significant structural rearrangement upon zinc binding supporting the idea that the binding site is ready to accommodate the metal. The interaction of SARS-CoV-2 Mpro with Zn2+ ion was also investigated by NMR. Moreover, zinc binding is able to inhibit protein activity, demonstrating that the zinc ion is capable of an efficient binding also in solution. These findings provide a solid ground for designing potent and selective inhibitors of SARS-CoV-2 Mpro suggesting that a zinc ion incorporated into suitable ligands interacting with additional sites at the protein surface can modulate the binding energy.

11.
FEBS Open Bio ; 12:286-287, 2022.
Article in English | EMBASE | ID: covidwho-1976637

ABSTRACT

Coronaviruses have emerged as important agents of human infection. SARS-CoV-2, the causative agent of COVID-19, has triggered a global pandemic with devastating consequences. The understanding of fundamental aspects of these viruses is of extreme importance. Fast vaccine development has been a crucial factor in preventing serious disease, but the fast-paced emergence of new variants raises many problems. Viral non-structural proteins are fundamental for viral replication. SARS-CoV-2 nsp16 is a 20-O-methyltransferase with a pivotal role in Interferon antagonism. Nsp16 methylates viral RNA to mimic the host mRNA and then the cell stops recognizing it as foreign. This activity is stimulated by the interaction with nsp10. This protein also acts as a co-factor for the exoribonucleolytic activity of nsp14. Nsp14 also has significant anti-interferon importance that stems from its 2 distinct activities: the N-terminal 3'-to-5' exoribonuclease (ExoN) and a C-terminal N7-methyltransferase (N7-MTase). Unlike Spike proteins, these nsp10, nsp14, and nsp16 are highly conserved among viral variants. In this work, we are studying them and finding inhibitors in order to develop new therapies. Nsp10 is the prime target of our focus since it is the central player in the regulation of both nsp14 and nsp16.

12.
Int J Mol Sci ; 23(15)2022 Jul 29.
Article in English | MEDLINE | ID: covidwho-1969293

ABSTRACT

Neuropilin 1 (NRP1) represents one of the two homologous neuropilins (NRP, splice variants of neuropilin 2 are the other) found in all vertebrates. It forms a transmembrane glycoprotein distributed in many human body tissues as a (co)receptor for a variety of different ligands. In addition to its physiological role, it is also associated with various pathological conditions. Recently, NRP1 has been discovered as a coreceptor for the SARS-CoV-2 viral entry, along with ACE2, and has thus become one of the COVID-19 research foci. However, in addition to COVID-19, the current review also summarises its other pathological roles and its involvement in clinical diseases like cancer and neuropathic pain. We also discuss the diversity of native NRP ligands and perform a joint analysis. Last but not least, we review the therapeutic roles of NRP1 and introduce a series of NRP1 modulators, which are typical peptidomimetics or other small molecule antagonists, to provide the medicinal chemistry community with a state-of-the-art overview of neuropilin modulator design and NRP1 druggability assessment.


Subject(s)
COVID-19 , Neoplasms , Animals , Humans , Neuropilin-1/chemistry , Neuropilin-1/genetics , Neuropilin-2/genetics , SARS-CoV-2
13.
Letters in Drug Design and Discovery ; 19(7):637-653, 2022.
Article in English | EMBASE | ID: covidwho-1968944

ABSTRACT

Background: Since the end of 2019, the etiologic agent SAR-CoV-2 responsible for one of the most significant epidemics in history has caused severe global economic, social, and health damages. The drug repurposing approach and application of Structure-based Drug Discovery (SBDD) using in silico techniques are increasingly frequent, leading to the identification of several molecules that may represent promising potential. Methods: In this context, here we use in silico methods of virtual screening (VS), pharmacophore modeling (PM), and fragment-based drug design (FBDD), in addition to molecular dynamics (MD), molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) calculations, and covalent docking (CD) for the identification of potential treatments against SARS-CoV-2. We initially validated the docking protocol followed by VS in 1,613 FDA-approved drugs obtained from the ZINC database. Thus, we identified 15 top hits, of which three of them were selected for further simulations. In parallel, for the compounds with a fit score value ≤ of 30, we performed the FBDD protocol, where we designed 12 compounds. Results: By applying a PM protocol in the ZINC database, we identified three promising drug candidates. Then, the 9 top hits were evaluated in simulations of MD, MM-PBSA, and CD. Subsequently, MD showed that all identified hits showed stability at the active site without significant changes in the pro-tein's structural integrity, as evidenced by the RMSD, RMSF, Rg, SASA graphics. They also showed interactions with the catalytic dyad (His41 and Cys145) and other essential residues for activity (Glu166 and Gln189) and high affinity for MM-PBSA, with possible covalent inhibition mechanism. Conclusion: Finally, our protocol helped identify potential compounds wherein ZINC896717 (Zafir-lukast), ZINC1546066 (Erlotinib), and ZINC1554274 (Rilpivirine) were more promising and could be explored in vitro, in vivo, and clinical trials to prove their potential as antiviral agents.

14.
Struct Chem ; : 1-18, 2022 Aug 01.
Article in English | MEDLINE | ID: covidwho-1966169

ABSTRACT

The novel coronavirus 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly worldwide, and new drug treatments for COVID-19 are urgently required. To find the potential inhibitors against the main protease (Mpro) of SARS-CoV-2, we investigated the inhibitory potential of naturally occurring compounds from the plants Moringa oleifera, Aloe vera, and Nyctanthes arbor-tristis, using molecular docking, classical molecular mechanics optimizations, and ab initio fragment molecular orbital (FMO) calculations. Of the 35 compounds that we simulated, feralolide from Aloe vera exhibited the highest binding affinity against Mpro. Therefore, we proposed novel compounds based on the feralolide and investigated their binding properties to Mpro. The FMO results indicated that the introduction of a hydroxyl group into feralolide significantly enhances its binding affinity to Mpro. These results provide useful information for developing potent Mpro inhibitors. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02021-y.

15.
Journal of the Academy of Consultation-Liaison Psychiatry ; 63:S68, 2022.
Article in English | EMBASE | ID: covidwho-1966674

ABSTRACT

Background: Due to COVID pandemic, there have been increased needs for ECMO circuits to support patients with respiratory failure1. Unfortunately, due to pharmacokinetics alteration of commonly used sedative and psychotropic medications by the ECMO circuits2,new sedation approaches to manage delirium and agitation is required. We present a case of COVID pneumonia patient on ECMO support, whose delirium symptoms were managed with a novel psychopharmacotherapy protocol. Case: Mr. M is a 57-year-old male patient with past medical history of obesity, hypertension, admitted to Stanford Hospital due to COVID pneumonia, complicated by respiratory failure, required to be on Veno-Venous ECMO support with bridge to transplant. He had significant hyperactive delirium with Richmond Agitation-Sedation Scale (RASS) score of +3 and ICDSC score of 7 for most of the days, despite heavy conventional pharmacological sedation. We observe the same problems with most patients placed on the ECMO system, leading to an investigation and development of a new protocol. Discussion: Patient on ECMO support requires adequate sedation to prevent clinical deterioration that can result from hyperactive delirium (ie., chugging, blood clots or decannulation)2. Nevertheless, ECMO circuit’s significant alterations of drug pharmacokinetics, such as increased volume of distribution and sequestration of lipophilic and protein bound medications, with no clear guidelines on managing sedation/delirium in patients with ECMO support at this time2, we conducted an extensive literature search and developed a novel protocol. This new sedation approach includes alpha-2 agonists, opioids, barbiturates and calcium channel modulators with the lowest lipophilicity and protein binding potential of each medication in its class4,5,thus overcoming the challenges introduced by ECMO circuits. The new protocol allowed the patient to participate in lung transplant work-up, physical therapy, and eventually facilitated receiving bilateral lung transplantation. Conclusion/Implications: ECMO is a life saving device that can help patient with cardiac-respiratory failure, and its use has been increasing in clinical practice. However, there needs to be an improvement in successful sedation/delirium management to minimize adverse events, and optimize the success of this lifesaving technologies. References: 1. Cho HJ, et al. ECMO use in COVID-19: lessons from past respiratory virus outbreaks-a narrative review. Crit Care. 2020 Jun 6;24(1):301 2. deBacker J, et al. Sedation Practice in Extracorporeal Membrane Oxygenation-Treated Patients with Acute Respiratory Distress Syndrome: A Retrospective Study. ASAIO J. 2018 Jul/Aug;64(4):544-551 3. Lemaitre F, et al. Propofol, midazolam, vancomycin and cyclosporine therapeutic drug monitoring in extracorporeal membrane oxygenation circuits primed with whole human blood. Crit Care. 2015;19(1):40 4. Hansch C, et al. Hydrophobicity and central nervous system agents: on the principle of minimal hydrophobicity in drug design. J Pharm Sci. 1987 Sep;76(9):663-87 5. Bockbrader HN, et al. A comparison of the pharmacokinetics and pharmacodynamics of pregabalin and gabapentin. Clin Pharmacokinet. 2010 Oct;49(10):661-9

16.
Int J Mol Sci ; 23(12)2022 Jun 16.
Article in English | MEDLINE | ID: covidwho-1963993

ABSTRACT

The need for preparing new strategies for the design of emergency drug therapies against COVID-19 and similar diseases in the future is rather urgent, considering the high rate of morbidity and especially mortality associated with COVID-19, which so far has exceeded 18 million lives. Such strategies could be conceived by targeting the causes and also the serious toxic side effects of the diseases, as well as associated biochemical and physiological pathways. Deferiprone (L1) is an EMA- and FDA-approved drug used worldwide for the treatment of iron overload and also other conditions where there are no effective treatments. The multi-potent effects and high safety record of L1 in iron loaded and non-iron loaded categories of patients suggests that L1 could be developed as a "magic bullet" drug against COVID-19 and diseases of similar symptomatology. The mode of action of L1 includes antiviral, antimicrobial, antioxidant, anti-hypoxic and anti-ferroptotic effects, iron buffering interactions with transferrin, iron mobilizing effects from ferritin, macrophages and other cells involved in the immune response and hyperinflammation, as well as many other therapeutic interventions. Similarly, several pharmacological and other characteristics of L1, including extensive tissue distribution and low cost of production, increase the prospect of worldwide availability, as well as many other therapeutic approach strategies involving drug combinations, adjuvant therapies and disease prevention.


Subject(s)
COVID-19 , Iron Overload , Adult , COVID-19/drug therapy , Deferiprone/therapeutic use , Humans , Iron/therapeutic use , Iron Chelating Agents/adverse effects , Iron Overload/chemically induced , Iron Overload/etiology , Pyridones/pharmacology , Pyridones/therapeutic use
17.
Molecules ; 27(10)2022 May 23.
Article in English | MEDLINE | ID: covidwho-1953751

ABSTRACT

The COVID-19 pandemic caused by SARS-CoV-2 is a global burden on human health and economy. The 3-Chymotrypsin-like cysteine protease (3CLpro) becomes an attractive target for SARS-CoV-2 due to its important role in viral replication. We synthesized a series of 8H-indeno[1,2-d]thiazole derivatives and evaluated their biochemical activities against SARS-CoV-2 3CLpro. Among them, the representative compound 7a displayed inhibitory activity with an IC50 of 1.28 ± 0.17 µM against SARS-CoV-2 3CLpro. Molecular docking of 7a against 3CLpro was performed and the binding mode was rationalized. These preliminary results provide a unique prototype for the development of novel inhibitors against SARS-CoV-2 3CLpro.


Subject(s)
COVID-19 , Protease Inhibitors , COVID-19/drug therapy , Cysteine Endopeptidases/chemistry , Humans , Molecular Docking Simulation , Pandemics , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacology , SARS-CoV-2 , Thiazoles/pharmacology , Viral Proteins/metabolism
18.
Front Pharmacol ; 13: 874746, 2022.
Article in English | MEDLINE | ID: covidwho-1952525

ABSTRACT

The SARS-CoV2 pandemic has highlighted the importance of efficient and effective methods for identification of therapeutic drugs, and in particular has laid bare the need for methods that allow exploration of the full diversity of synthesizable small molecules. While classical high-throughput screening methods may consider up to millions of molecules, virtual screening methods hold the promise of enabling appraisal of billions of candidate molecules, thus expanding the search space while concurrently reducing costs and speeding discovery. Here, we describe a new screening pipeline, called drugsniffer, that is capable of rapidly exploring drug candidates from a library of billions of molecules, and is designed to support distributed computation on cluster and cloud resources. As an example of performance, our pipeline required ∼40,000 total compute hours to screen for potential drugs targeting three SARS-CoV2 proteins among a library of ∼3.7 billion candidate molecules.

19.
Comput Biol Chem ; 98: 107694, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1944667

ABSTRACT

The COVID-19 has a worldwide spread, which has prompted concerted efforts to find successful drug treatments. Drug design focused on finding antiviral therapeutic agents from plant-derived compounds which may disrupt the attachment of SARS-CoV-2 to host cells is with a pivotal need and role in the last year. Herein, we provide an approach based on drug design methods combined with machine learning approaches to classify and discover inhibitors for COVID-19 from natural products. The spike receptor-binding domain (RBD) was docked with database of 125 ligands. The docking protocol based on several steps was performed within Autodock Vina to identify the high-affinity binding mode and to reveal more insights into interaction between the phytochemicals and the RBD domain. A protein-ligand interaction analyzer has been developed. The drug-likeness properties of explored inhibitors are analyzed in the frame of exploratory data analyses. The developed computational protocol yielded a comprehensive pipeline for predicting the inhibitors to prevent the entry RBD region.


Subject(s)
Antiviral Agents , COVID-19 , Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Biological Products/chemistry , Biological Products/pharmacology , COVID-19/drug therapy , Drug Evaluation, Preclinical , Humans , Ligands , Molecular Docking Simulation , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/metabolism
20.
Trends Biotechnol ; 40(8): 987-1003, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1931129

ABSTRACT

Industry 4.0 encompasses a new industrial revolution in which advanced manufacturing systems are interconnected with information technologies. These sophisticated data-gathering technologies have led to a shift toward smarter manufacturing processes involving the use of smart materials (SMs). The properties of SMs make them highly attractive for numerous biomedical applications. The integration of artificial intelligence (AI) enables them to be effectively used in the design of novel biomedical platforms to overcome shortcomings in the current biotechnology industry. This review summarizes recent advances in AI-assisted SMs for different healthcare products. The current challenges and future perspectives of AI-supported smart biosystems are also discussed, particularly with the regard to their applications in drug design, biosensors, theranostics, and electronic skins.


Subject(s)
Biosensing Techniques , Wearable Electronic Devices , Artificial Intelligence , Biotechnology , Precision Medicine
SELECTION OF CITATIONS
SEARCH DETAIL