Geraniol and Citral as potential therapeutic agents targeting the HSP90 activity: An in silico and experimental approach

Since December 2019, the worldwide spread of COVID-19 has brought the majority of the world to a standstill, affecting daily lives as well as economy. Under these conditions, it is imperative to develop a cure as soon as possible. On account of some of the adverse side effects of the existing conventional drugs, researchers all around the world are screening natural antiviral phytochemicals as potential therapeutic agents against COVID-19. This paper aims to review interactions of some specific phytochemicals with the receptor binding domain (RBD) of the Spike glycoprotein of SARS-CoV-2 and suggest their possible therapeutic applications. Literature search was done based on the wide array of in-silico studies conducted using broad spectrum phytochemicals against SARS-CoV-2 and other viruses. We shortlisted 26 such phytochemicals specifically targeting the S protein and its interactions with host receptors. To validate the previously published results, we also conducted molecular docking using the AutoDockVina application and identified 6 high potential phytochemicals for therapeutic use based on their binding energies. Besides this, availability of these compounds, their mode of action, toxicity data and cost-effectiveness were also taken into consideration. Our review specifically identifies 6 phytochemicals that can be used as potential treatments for COVID-19 based on their availability, toxicology results and low costs of production. However, all these compounds need to be further validated by wet lab experiments and should be approved for clinical use only after appropriate trials.

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Identification of promising drug candidates against Non-Structural Protein 15 (NSP15) from SARS-CoV-2: an in silico assisted drug-repurposing studies

10.26434/chemrxiv.12407711 ◽

2020 ◽

Author(s):

Rameez Jabeer Khan ◽

Rajat Kumar Jha ◽

Ekampreet Singh ◽

Monika Jain ◽

Gizachew Muluneh Amera ◽

...

Keyword(s):

Free Energy ◽

In Silico ◽

Binding Free Energy ◽

Drug Repurposing ◽

Md Simulations ◽

Therapeutic Agents ◽

Global Dynamics ◽

Host Immune System ◽

Structural Protein ◽

Drug Candidates

<div>The recent COVID-19 pandemic caused by SARS-CoV-2 has recorded a high number of infected people across the globe. The notorious nature of the virus makes it necessary for us to identify promising therapeutic agents in a time-sensitive manner. The current study utilises an <i>in silico</i> based drug repurposing approach to identify potential drug candidates targeting non-structural protein 15 (NSP15), i.e. a uridylate specific endoribonuclease of SARS-CoV-2</div><div>which plays an indispensable role in RNA processing and viral immune evasion from the host immune system. NSP15 was screened against an in-house library of 123 antiviral drugs obtained from the DrugBank database from which three promising drug candidates were identified based on their estimated free energy of binding (<i>ΔG</i>), estimated inhibition constant (<i>Ki</i>), the orientation of drug molecules in the active site and the key interacting residues of</div><div>NSP15. The MD simulations were performed for the selected NSP15-drug complexes along with free protein to mimic on their physiological state. The binding free energies of the selected NSP15-drug complexes were also calculated using the trajectories of MD simulations of NSP15-drug complexes through MM/PBSA (Molecular Mechanics with Poisson-Boltzmann and surface area solvation) approach where NSP15-Simeprevir (-242.559 kJ/mol) and NSP15-Paritaprevir (-149.557 kJ/mol) exhibited the strongest binding affinities. Together with the results of molecular docking, global dynamics, essential dynamics and binding free energy analysis, we propose that Simeprevir and Paritaprevir are promising drug candidates for the inhibition of NSP15 and could act as potential therapeutic agents against SARS-CoV-2.</div>

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Artificial Intelligence Guided De Novo Molecular Design Targeting COVID-19

10.26434/chemrxiv.12581075 ◽

2020 ◽

Author(s):

Srilok Srinivasan ◽

Rohit Batra ◽

Henry Chan ◽

Ganesh Kamath ◽

Mathew J. Cherukara ◽

...

Keyword(s):

Artificial Intelligence ◽

In Silico ◽

High Throughput Screening ◽

De Novo ◽

Molecular Design ◽

Chemical Space ◽

Computational Cost ◽

Ligand Design ◽

Therapeutic Agents ◽

Docking Simulations

An extensive search for active therapeutic agents against the SARS-CoV-2 is being conducted across the globe. Computational docking simulations have traditionally been used for <i>in silico</i> ligand design and remain popular method of choice for high-throughput screening of therapeutic agents in the fight against COVID-19. Despite the vast chemical space (millions to billions of biomolecules) that can be potentially explored as therapeutic agents, we remain severely limited in the search of candidate compounds owing to the high computational cost of these ensemble docking simulations employed in traditional <i>in silico</i> ligand design. Here, we present a <i>de novo</i> molecular design strategy that leverages artificial intelligence to discover new therapeutic biomolecules against SARS-CoV-2. A Monte Carlo Tree Search algorithm combined with a multi-task neural network (MTNN) surrogate model for expensive docking simulations and recurrent neural networks (RNN) for rollouts, is used to sample the exhaustive SMILES space of candidate biomolecules. Using Vina scores as target objective to measure binding of therapeutic molecules to either the isolated spike protein (S-protein) of SARS-CoV-2 at its host receptor region or to the S-protein:Angiotensin converting enzyme 2 (ACE2) receptor interface, we generate several (~100's) new biomolecules that outperform FDA (~1000’s) and non-FDA biomolecules (~million) from existing databases. A transfer learning strategy is deployed to retrain the MTNN surrogate as new candidate molecules are identified - this iterative search and retrain strategy is shown to accelerate the discovery of desired candidates. We perform detailed analysis using Lipinski's rules and also analyze the structural similarities between the various top performing candidates. We spilt the molecules using a molecular fragmenting algorithm and identify the common chemical fragments and patterns – such information is important to identify moieties that are responsible for improved performance. Although we focus on therapeutic biomolecules, our AI strategy is broadly applicable for accelerated design and discovery of any chemical molecules with user-desired functionality.

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MicroRNA Editing Detection and Function: A Combined In Silico and Experimental Approach for the Identification and Validation of Putative Oncogenic Targets

Methods in Molecular Biology - RNA Editing ◽

10.1007/978-1-0716-0787-9_15 ◽

2020 ◽

pp. 253-267

Author(s):

Valentina Tassinari ◽

Valeriana Cesarini ◽

Domenico Alessandro Silvestris ◽

Andrea Scafidi ◽

Lorenzo Cucina ◽

...

Keyword(s):

In Silico ◽

Experimental Approach ◽

And Function

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Discovery of a “Cocktail” of Potential SARS-COV-2 Main Protease Inhibitors through Virtual Screening of Known Chemical Components of Vitex negundo L. (“Lagundi”)

Medicinal Chemistry ◽

10.2174/1573406417666210618132003 ◽

2021 ◽

Vol 17 ◽

Author(s):

Ruel Cayona ◽

Evelyn Creencia

Keyword(s):

Clinical Trials ◽

Virtual Screening ◽

Medicinal Plants ◽

In Silico ◽

Development Program ◽

Therapeutic Agents ◽

The Philippines ◽

Vitex Negundo ◽

Main Protease ◽

Donor And Acceptor

Aim: The prevailing crisis caused by the COVID-19 pandemic demands the development of effective therapeutic agents that can be implemented with minimal to zero adverse effects. Background: Vitex negundo L. (VNL) is a medicinal plant with reported efficacy against respiratory diseases and some of the COVID-19 symptoms. Funded by the Department of Science and Technology (DOST), the University of the Philippines – Philippine General Hospital (UP-PGH) is currently conducting clinical trials of VNL and other medicinal plants as adjuvant therapeutic agents against mild cases of COVID-19. The basis for the clinical trials is primarily the pharmacological efficacy of the medicinal plants against respiratory disorders and associated COVID-19 symptoms. Objective: This study assessed the in silico potential of VNL components against SARS-CoV-2 main protease (Mpro), an enzyme that plays an important role in COVID-19, the disease caused by the SARS-CoV-2. Objective: This study assessed the in silico potential of VNL components against SARS-CoV-2 main protease (Mpro), an enzyme that plays an important role in COVID-19, the disease caused by the SARS-CoV-2. Method: Phytochemical mining of VNL components from the literature was conducted. A database consisting of 250 known compounds from different parts of VNL was created and screened against SARS-CoV-2 Mpro using the PyRx virtual screening tool. The most promising components were further subjected to in silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses using the SwissADME web server and Toxtree software. Results: Virtual screening revealed that 102 VNL components in the database had comparable to or better binding affinities toward SARS-COV-2 Mpro than known chemical inhibitors (e.g. N3 and carmofur). It was determined that the active site of SARS-CoV-2 Mpro receptor consists of multiple H-donor and acceptor sites; hence, the most stable receptor-ligand complexes are generally formed by VNL ligands that establish effective H-bonding with the SARS-CoV-2 Mpro. The promising components, representing a “cocktail” of potential inhibitors also revealed interesting ADMET properties. Conclusion: This in silico study identified VNL as a potential single source of a cocktail of SARS-CoV-2 Mpro inhibitors and a promising adjuvant therapeutic agent against COVID-19 or its symptoms. Furthermore, the study offers a rationale on phytochemical mining from medicinal plants as a means that can be implemented in the early stage of a drug discovery and development program.

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Synthesis and in silico study of 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives as suitable therapeutic agents

Brazilian Journal of Pharmaceutical Sciences ◽

10.1590/s2175-97902017000115237 ◽

2017 ◽

Vol 53 (1) ◽

Cited By ~ 1

Author(s):

Ghulam Hussain ◽

Muhammad Athar Abbasi ◽

Aziz-ur-Rehman ◽

Sabahat Zahra Siddiqui ◽

Syed Adnan Ali Shah ◽

...

Keyword(s):

In Silico ◽

Therapeutic Agents ◽

In Silico Study

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Liposomal Formulations for an Efficient Encapsulation of Epigallocatechin-3-Gallate: An In-Silico/Experimental Approach

Molecules ◽

10.3390/molecules23020441 ◽

2018 ◽

Vol 23 (2) ◽

pp. 441 ◽

Cited By ~ 12

Author(s):

Emiliano Laudadio ◽

Cristina Minnelli ◽

Adolfo Amici ◽

Luca Massaccesi ◽

Giovanna Mobbili ◽

...

Keyword(s):

In Silico ◽

Experimental Approach ◽

Liposomal Formulations

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Heterodimer Formation within Universal Stress Protein Classes Revealed By an In Silico and Experimental Approach

Journal of Molecular Biology ◽

10.1016/j.jmb.2008.04.074 ◽

2008 ◽

Vol 380 (2) ◽

pp. 340-350 ◽

Cited By ~ 13

Author(s):

Laurence Nachin ◽

Lars Brive ◽

Karin-Cecilia Persson ◽

Peder Svensson ◽

Thomas Nyström

Keyword(s):

In Silico ◽

Experimental Approach ◽

Stress Protein ◽

Universal Stress Protein ◽

Protein Classes

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Integrated in Silico and Experimental Approach towards the Design of a Novel Recombinant Protein Containing an Anti-HER2 scFv

International Journal of Molecular Sciences ◽

10.3390/ijms22073547 ◽

2021 ◽

Vol 22 (7) ◽

pp. 3547

Author(s):

Joana Santos ◽

Miguel Cardoso ◽

Irina S. Moreira ◽

João Gonçalves ◽

João D. G. Correia ◽

...

Keyword(s):

Recombinant Protein ◽

Recombinant Proteins ◽

In Silico ◽

Experimental Approach ◽

Antibody Fragment ◽

Cost Effective ◽

Docking Studies ◽

Single Chain ◽

In Silico Studies ◽

Molecular Modeling And Docking

Biological therapies, such as recombinant proteins, are nowadays amongst the most promising approaches towards precision medicine. One of the most innovative methodologies currently available aimed at improving the production yield of recombinant proteins with minimization of costs relies on the combination of in silico studies to predict and deepen the understanding of the modified proteins with an experimental approach. The work described herein aims at the design and production of a biomimetic vector containing the single-chain variable domain fragment (scFv) of an anti-HER2 antibody fragment as a targeting motif fused with HIV gp41. Molecular modeling and docking studies were performed to develop the recombinant protein sequence. Subsequently, the DNA plasmid was produced and HEK-293T cells were transfected to evaluate the designed vector. The obtained results demonstrated that the plasmid construction is robust and can be expressed in the selected cell line. The multidisciplinary integrated in silico and experimental strategy adopted for the construction of a recombinant protein which can be used in HER2+-targeted therapy paves the way towards the production of other therapeutic proteins in a more cost-effective way.

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