A Review on Artificial Intelligence Approaches and Rational Approaches in Drug Discovery.

Artificial intelligence (AI) speeds up the drug development process and reduces its time, as well as the cost which is of enormous importance in outbreaks such as COVID-19. It uses a set of machine learning algorithms that collects the available data from resources, categorises, processes and develops novel learning methodologies. Virtual screening is a successful application of AI, which is used in screening huge drug-like databases and filtering to a small number of compounds. The brain's thinking of AI is its neural networking which uses techniques such as Convoluted Neural Network (CNN), Recursive Neural Network (RNN) or Generative Adversial Neural Network (GANN). The application ranges from small molecule drug discovery to the development of vaccines. In the present review article, we discussed various techniques of drug design, structure and ligand-based, pharmacokinetics and toxicity prediction using AI. The rapid phase of discovery is the need of the hour and AI is a targeted approach to achieve this.

Identification of potential edible mushroom as SARS-CoV-2 main protease inhibitor using rational drug designing approach.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is highly pathogenic to humans and has created health care threats worldwide. This urgent situation has focused the researchers worldwide towards the development of novel vaccine or small molecule therapeutics for SARS-CoV-2. Although several vaccines have already been discovered and are in use for the masses, no therapeutic medication has yet been approved by FDA for the treatment of COVID-19. Keeping this in view, in the present study, we have identified promising hits against the main protease (Mpro) of SARS-CoV-2 from edible mushrooms. Structure-based virtual screening (VS) of 2433 compounds derived from mushrooms was performed with Mpro protein (6LU7). Four promising hits, namely, Kynapcin-12 (M_78), Kynapcin-28 (M_82), Kynapcin-24 (M_83), and Neonambiterphenyls-A (M_366) were identified based on the result of docking, Lipinski's rule, 100 ns molecular dynamics (MD) simulation and MM/PBSA binding free energy calculations. Finally, the inhibitory properties of these hits were compared with three known inhibitors, baicalein (1), baicalin (2), and biflavonoid (3). Data indicated that M_78, M_82 and M_83 compounds present in edible mushroom Polyozellus multiplex were potent inhibitors of Mproprotein (6LU7). It could be concluded that edible mushroom Polyozellus multiplex has potential activity against SARS-CoV-2 infection and identified molecules could be further explored as therapeutic inhibitors against SARS-CoV-2.

Structure-Based Virtual Screening and Molecular Dynamics Simulation to Identify Potential SARS-CoV-2 Spike Receptor Inhibitors from Natural Compound Database.

The outbreak of respiratory disease, COVID-19 caused by SARS-CoV-2 has now been spread globally and the number of new infections is rising every moment. There are no specific medications that are currently available to combat the disease. The spike receptor of SARS-CoV-2 facilitates the viral entry into a host cell and initiation of infection. Targeting the viral entry at the initial stage has a better advantage than inhibiting it in later stages of the viral life cycle. This study deals with identification of the potential natural molecule or its derivatives from MolPort Databank as SARS-CoV-2 spike receptor inhibitors using structure-based virtual screening followed by molecular dynamics simulation. On the basis of ADME properties, docking score, MMGBSAbinding energy, 150 ns molecular docking studies, and final molecular dynamics analysis, two natural compounds - 3 (MolPort-002-535-004) docking score -9.10 kcal mol-1 and 4 (MolPort-005-910-183) docking score -8.5 kcal mol-1, are selected as potential in-silico spike receptor inhibitors. Both hits are commercially available and can be further used for in-vitro and in-vivo studies. Findings of this study can facilitate rational drug design against SARS-CoV-2 spike receptor.

Phytochemicals of Zingiberaceae family exhibit potentiality against SARS-CoV-2 main protease identified by a rational computer-aided drug design.

Coronavirus disease 2019 (COVID-19) has created huge social, economic and human health crises globally. Discovery of specific drugs has become a new challenge to the researcher. Structure-based virtual-screening of our in-house databank containing1102 phytochemicals of Zingiberaceae family was performed with main protease(Mpro), a crucial enzyme of SARS-CoV-2. Rigorous docking and ADME study of top-scored twenty hits resulted from VS was performed. Then 100 ns molecular dynamics followed by MMPBSA binding free energy(ΔGbind) calculation of A280 and KZ133 was also performed. These two hits showed good interactions with crucial amino acid residues of Mpro HIS-41 and CYS-145, excellent ADME properties, fair ΔGbind values (> ‒188.03 kj/mol), and average protein-ligand complex RMSD < apo-protein RMSD. Therefore, the seed extracts of Alpinia blepharocalyx and rhizome extracts Kaempferia angustifolia containing A280 and KZ133, respectively, may be useful against COVID-19 after the proper biological screening. These two novel scaffolds could be exploited as potent SARS-CoV-2-Mpro inhibitors.

Identification of SARS-CoV-2 Main Protease Inhibitors Using Structure Based Virtual Screening and Molecular Dynamics Simulation of DrugBank Database.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly pathogenic to humans and has created an unprecedented global health care threat. Globally, intense efforts are going on to discover a vaccine or new drug molecules to control the COVID-19. However, till today, there is no effective therapeutics or treatment available for COVID-19. In this study, we aim to find out potential small molecule inhibitors for SARS-CoV-2 main protease (Mpro) from the known DrugBank database version 5.1.8. We applied structure-based virtual screening of the database containing 11875 numbers of drug candidates to identify potential hits for SARS-CoV-2 Mpro inhibitors. Seven potential inhibitors having admirable XP glide score ranging from -15.071 to -8.704 kcal/mol and good binding affinity with the active sites amino acids of Mpro were identified. The selected hits were further analyzed with 50 ns molecular dynamics (MD) simulation to examine the stability of protein-ligand complexes. The root mean square deviation and potential energy plot indicates the stability of the complexes during the 50 ns MD simulation. The MM-GBSA analysis also showed good binding energy of the selected hits (-83.2718 to -58.6618 kcal/mol). Further analysis revealed critical hydrogen bonds and hydrophobic interactions between compounds and the target protein. The compounds bind to biologically important regions of Mpro, indicating their potential to inhibit the functionality of this component.

Potentiality of Moringa oleifera against SARS-CoV-2: identified by a rational computer aided drug design method.

Coronavirus disease 2019 (COVID-19) has created a global human health crisis and economic setbacks. Lack of specific therapeutics and limited treatment options against COVID-19 has become a new challenge to identify potential hits in order to develop new therapeutics. One of the crucial life cycle enzymes of SARS-CoV-2 is main protease (Mpro), which plays a major role in mediating viral replication, makes it an attractive drug target. Virtual screening and three times repeated 100 ns molecular dynamics simulation of the best hits were performed to identify potential SARS-CoV-2 Mpro inhibitors from the available compounds of an antiviral plant Moringa oleifera. Three flavonoids isorhamnetin (1), kaempferol (2) and apigenin (3) showed good binding affinity, stable protein-ligand complexes throughout the simulation time, high binding energy and similar binding poses in comparison with known SARS-CoV-2 Mpro inhibitor baicalein. Therefore, different parts of M. oleifera may be emerged as a potential preventive and therapeutic against COVID-19.

Identification of potential inhibitors of SARS-CoV-2 main protease and spike receptor from 10 important spices through structure-based virtual screening and molecular dynamic study.

The outbreak of novel coronavirus disease (COVID-19) caused by SARS-CoV-2 poses a serious threat to human health and world economic activity. There is no specific drug for the treatment of COVID-19 patients at this moment. Traditionally, people have been using spices like ginger, fenugreek and onion, etc. for the remedy of a common cold. This work identifies the potential inhibitors of the main protease (Mpro) and spike (S) receptor of SARS-CoV-2 from 10 readily available spices. These two proteins, S and Mpro, play an important role during the virus entry into the host cell, and replication and transcription processes of the virus, respectively. To identify potential molecules an in-house databank containing 1040 compounds was built-up from the selected spices. Structure-based virtual screening of this databank was performed with two important SARS-CoV-2 proteins using Glide. Top hits resulted from virtual screening (VS) were subjected to molecular docking using AutoDock 4.2 and AutoDock Vina to eliminate false positives. The top six hits against Mpro and top five hits against spike receptor subjected to 130 ns molecular dynamic simulation using GROMACS. Finally, the compound 1-, 2-, 3- and 5-Mpro complexes, and compound 17-, 18-, 19-, 20- and 21- spike receptor complexes showed stability throughout the simulation time. The ADME values also supported the drug-like nature of the selected hits. These nine compounds are available in onion, garlic, ginger, peppermint, chili and fenugreek. All the spices are edible and might be used as home remedies against COVID-19 after proper biological evaluation.

In silico analysis and identification of promising hits against 2019 novel coronavirus 3C-like main protease enzyme.

The recent outbreak of the 2019 novel coronavirus disease (COVID-19) has been proved as a global threat. No particular drug or vaccine has not yet been discovered which may act specifically against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and causes COVID-19. For this highly infectious virus, 3CL-like main protease (3CLpro) plays a key role in the virus life cycle and can be considered as a pivotal drug target. Structure-based virtual screening of DrugBank database resulted in 20 hits against 3CLpro. Atomistic 100 ns molecular dynamics of five top hits and binding energy calculation analyses were performed for main protease-hit complexes. Among the top five hits, Nafarelin and Icatibant affirmed the binding energy (g_MMPBSA) of -712.94 kJ/mol and -851.74 kJ/mol, respectively. Based on binding energy and stability of protein-ligand complex; the present work reports these two drug-like hits against SARS-CoV-2 main protease.Communicated by Ramaswamy H. Sarma.