Cheminformatics-aided discovery of potential allosteric site modulators of ubiquitin-specific protease 7.

Ubiquitin-specific peptidase 7 (USP7) is a deubiquitinating enzyme that mediates the stability and activity of numerous proteins. At basal expression levels, USP7 stabilizes p53 protein, even in the presence of excess MDM2. However, its overexpression leads to the deubiquitination of MDM2 at a rate faster than p53, leading to p53 degradation and pro-tumorigenic roles. Consequently, it is an attractive target for anticancer drug discovery via the modulation of its allosteric site from which the protein is activated. In this study, molecular modeling techniques and cheminformatics approaches were employed to unravel the potential of eighty compounds to serve as its allosteric site modulators. The compounds were initially subjected to virtual screening. Subsequently, the binding free energies of the top four compounds with the highest binding affinities were calculated, and their drug-likeness, and pharmacokinetic and toxicity profiles were evaluated. Ultimately, the complexes of the protein and hit compounds were subjected to a 100 nanoseconds (ns) molecular dynamics simulation. The results of the study revealed eight compounds from the compound library with docking scores ranging from - 7.491 to -11.43 kcal/mol, compared to P217564, which exhibited a docking score of -5.671 kcal/mol. The top four compounds with the highest affinities possessed drug-like properties, and good pharmacokinetic and toxicity profiles, and their predicted inhibitory potentials showed they will be effective at minimal concentration. Also, molecular dynamics simulation confirmed the stability of the protein-ligand complexes. Conclusively, the compounds identified in this study are worthy of further evaluation for the development of allosteric site modulators of USP7.

Phytochemical Analysis and Evaluation of Antioxidant and Antimicrobial Properties of Essential Oils and Seed Extracts of Anethum graveolens from Southern Morocco: In Vitro and In Silico Approach for a Natural Alternative to Synthetic Preservatives.

Anethum graveolens is an aromatic plant traditionally used as an antispasmodic and carminative. The objective of this study is to analyze the chemical composition of the essential oils and extracts obtained from seeds gathered in Errachidia, southern Morocco. Additionally, the antioxidant and antimicrobial properties of these oils and extracts will be evaluated. GC-MS analysis of the EO isolated by hydrodistillation revealed that its main compounds were E-anethole (38.13%), estragole (29.32%), fenchone (17.21%), and α-pinene (7.37%). The phenolic components were extracted using the methods of decoction and Soxhlet. The assay of the phenolic compounds showed that A. graveolens seeds contained considerable amounts of polyphenols, flavonoids, and condensed tannins, with variable levels depending on the extract analyzed. HPLC/UV-ESI-MS analyses performed on the decoction revealed a structural diversity of the molecules present in this extract, the most important of which were umbelliferone (12.35%), 3-hydroxyflavone (11.23%), rosmanol (8.95%), biotin (8.36%), emmotin H (4.91%), and coumarin (4.21%). The antioxidant activity, as determined by three techniques (DPPH•, FRAP, and CAT), demonstrated that the essential oils (EOs) and extracts had a potent capacity to counteract detrimental free radicals, control the generation of reactive oxygen species, and mitigate oxidative damages. The antimicrobial activity of the Eos and extracts was carried out in a liquid medium against five strains (E. cloacae, K. pneumoniae, E. coli, S. aureus, and S. epidermidis) and four candidiasis (C. albicans, C. dubliniensis, C. tropicalis, and C. parapsilosis) and Aspergillus niger. The results showed the effectiveness of the EOs compared to the aqueous, ethanolic, and decoction extracts against most of the microorganisms tested. In addition, the ethanolic extract showed antifungal activity that was distinguished from that of the other extracts. The antimicrobial efficacy of the essential oils under study can primarily be attributed to the synergistic interactions among its three principal constituents (E-anethole, estragole, and fenchone). Furthermore, molecular docking and molecular dynamics simulation results reveal significant interactions and stability between the selected bioactive compounds and different target proteins involved in antimicrobial and antioxidant activities. Compounds like 3-hydroxyflavone, emmotin H, trans-caftaric acid, methyl rosmarinate, 1-caffeoyl-beta-D-glucose, and kaempferol exhibited better binding energies with the explored proteins, indicating their potential as antimicrobial and antioxidant agents. Finally, our findings emphasize the significance of A. graveolens seeds as a promising reservoir of advantageous health compounds that can serve as organic substitutes for the presently employed synthetic preservatives.

QSAR, ADMET, molecular docking, and dynamics studies of 1,2,4-triazine-3(2H)-one derivatives as tubulin inhibitors for breast cancer therapy.

Breast cancer remains a leading cause of cancer-related deaths among women globally, necessitating the development of more effective therapeutic agents with minimal side effects. This study explores novel 1,2,4-triazine-3(2H)-one derivatives as potential inhibitors of Tubulin, a pivotal protein in cancer cell division, highlighting a targeted approach in cancer therapy. Using an integrated computational approach, we combined quantitative structure-activity relationship (QSAR) modeling, ADMET profiling, molecular docking, and molecular dynamics simulations to evaluate and predict the efficacy and stability of these compounds. Our QSAR models, developed through rigorous statistical analysis, revealed that descriptors such as absolute electronegativity and water solubility significantly influence inhibitory activity, achieving a predictive accuracy (R2) of 0.849. Molecular docking studies identified compounds with high binding affinities, particularly Pred28, which exhibited the best docking score of - 9.6 kcal/mol. Molecular dynamics simulations conducted over 100 ns provided further insights into the stability of these interactions. Pred28 demonstrated notable stability, with the lowest root mean square deviation (RMSD) of 0.29 nm and root mean square fluctuation (RMSF) values indicative of a tightly bound conformation to Tubulin. The novelty of this work lies in its methodological rigor and the integration of multiple advanced computational techniques to pinpoint compounds with promising therapeutic potential. Our findings advance the current understanding of Tubulin inhibitors and open avenues for the synthesis and experimental validation of these compounds, aiming to offer new solutions for breast cancer treatment.

Antibiotic discovery with artificial intelligence for the treatment of Acinetobacter baumannii infections.

Global challenges presented by multidrug-resistant Acinetobacter baumannii infections have stimulated the development of new treatment strategies. We reported that outer membrane protein W (OmpW) is a potential therapeutic target in A. baumannii. Here, a library of 11,648 natural compounds was subjected to a primary screening using quantitative structure-activity relationship (QSAR) models generated from a ChEMBL data set with >7,000 compounds with their reported minimal inhibitory concentration (MIC) values against A. baumannii followed by a structure-based virtual screening against OmpW. In silico pharmacokinetic evaluation was conducted to assess the drug-likeness of these compounds. The ten highest-ranking compounds were found to bind with an energy score ranging from -7.8 to -7.0 kcal/mol where most of them belonged to curcuminoids. To validate these findings, one lead compound exhibiting promising binding stability as well as favorable pharmacokinetics properties, namely demethoxycurcumin, was tested against a panel of A. baumannii strains to determine its antibacterial activity using microdilution and time-kill curve assays. To validate whether the compound binds to the selected target, an OmpW-deficient mutant was studied and compared with the wild type. Our results demonstrate that demethoxycurcumin in monotherapy and in combination with colistin is active against all A. baumannii strains. Finally, the compound was found to significantly reduce the A. baumannii interaction with host cells, suggesting its anti-virulence properties. Collectively, this study demonstrates machine learning as a promising strategy for the discovery of curcuminoids as antimicrobial agents for combating A. baumannii infections. IMPORTANCE: Acinetobacter baumannii presents a severe global health threat, with alarming levels of antimicrobial resistance rates resulting in significant morbidity and mortality in the USA, ranging from 26% to 68%, as reported by the Centers for Disease Control and Prevention (CDC). To address this threat, novel strategies beyond traditional antibiotics are imperative. Computational approaches, such as QSAR models leverage molecular structures to predict biological effects, expediting drug discovery. We identified OmpW as a potential therapeutic target in A. baumannii and screened 11,648 natural compounds. We employed QSAR models from a ChEMBL bioactivity data set and conducted structure-based virtual screening against OmpW. Demethoxycurcumin, a lead compound, exhibited promising antibacterial activity against A. baumannii, including multidrug-resistant strains. Additionally, demethoxycurcumin demonstrated anti-virulence properties by reducing A. baumannii interaction with host cells. The findings highlight the potential of artificial intelligence in discovering curcuminoids as effective antimicrobial agents against A. baumannii infections, offering a promising strategy to address antibiotic resistance.

A Study of the Synergistic Effects of Essential Oils from Origanum compactum and Origanum elongatum with Commercial Antibiotics against Highly Prioritized Multidrug-Resistant Bacteria for the World Health Organization.

The irrational use of antibiotics has favored the emergence of resistant bacteria, posing a serious threat to global health. To counteract antibiotic resistance, this research seeks to identify novel antimicrobials derived from essential oils that operate through several mechanisms. It aims to evaluate the quality and composition of essential oils from Origanum compactum and Origanum elongatum; test their antimicrobial activity against various strains; explore their synergies with commercial antibiotics; predict the efficacy, toxicity, and stability of compounds; and understand their molecular interactions through docking and dynamic simulations. The essential oils were extracted via hydrodistillation from the flowering tops of oregano in the Middle Atlas Mountains in Morocco. Gas chromatography combined with mass spectrometry (GC-MS) was used to examine their composition. Nine common antibiotics were chosen and tested alone or in combination with essential oils to discover synergistic effects against clinically important and resistant bacterial strains. A comprehensive in silico study was conducted, involving molecular docking and molecular dynamics simulations (MD). O. elongatum oil includes borneol (8.58%), p-cymene (42.56%), thymol (28.43%), and carvacrol (30.89%), whereas O. compactum oil is mostly composed of γ-terpinene (22.89%), p-cymene (15.84%), thymol (10.21%), and (E)-caryophyllene (3.63%). With O. compactum proving to be the most potent, these essential oils showed antibacterial action against both Gram-positive and Gram-negative bacteria. Certain antibiotics, including ciprofloxacin, ceftriaxone, amoxicillin, and ampicillin, have been shown to elicit synergistic effects. To fight resistant bacteria, the essential oils of O. compactum and O. elongatum, particularly those high in thymol and (E)-caryophyllene, seem promising when combined with antibiotics. These synergistic effects could result from their ability to target the same bacterial proteins or facilitate access to target sites, as suggested by molecular docking simulations. Molecular dynamics simulations validated the stability of the examined protein-ligand complexes, emphasizing the propensity of substances like thymol and (E)-caryophyllene for particular target proteins, opening the door to potentially effective new therapeutic approaches against pathogens resistant to multiple drugs.

Potent VEGFR-2 inhibitors for resistant breast cancer: a comprehensive 3D-QSAR, ADMET, molecular docking and MMPBSA calculation on triazolopyrazine derivatives.

More people are being diagnosed with resistant breast cancer, increasing the urgency of developing new effective treatments. Several lines of evidence suggest that blocking the kinase activity of VEGFR-2 reduces angiogenesis and slows tumor growth. In this study, we developed novel VEGFR-2 inhibitors based on the triazolopyrazine template by using comparative molecular field analysis (CoMFA) and molecular similarity indices (CoMSIA) models for 3D-QSAR analysis of 23 triazolopyrazine-based compounds against breast cancer cell lines (MCF -7). Both CoMFA (Q2 = 0.575; R 2 = 0.936, Rpred 2 = 0.956) and CoMSIA/SE (Q2 = 0.575; R 2 = 0.936, Rpred 2 = 0.847) results demonstrate the robustness and stability of the constructed model. Six novel compounds with potent inhibitory activity were carefully designed, and screening of ADMET properties revealed their good oral bioavailability and ability to diffuse through various biological barriers. When compared with the most active molecule in the data set and with Foretinib (breast cancer drug), molecular docking revealed that the six designed compounds had strengthened affinity (-8.9 to -10 kcal/mol) to VEGFR-2. Molecular Dynamics Simulations and MMPBSA calculations were applied to the selected compound T01 with the highest predicted inhibitory activity, confirming its stability in the active pocket of VEGFR-2 over 100 ns. The present results provided the basis for the chemical synthesis of new compounds with improved inhibitory properties against the breast cancer cell line (MCF -7).

Novel APOE Mutation in a Moroccan Subject Suffering from Alzheimer Disease: A Case Study and Exploration of Pathogenic Implication.

Alzheimer disease (AD) is a major public health concern worldwide. It is a severe neurodegenerative disease that primarily affects the elderly and causes significant brain cell death. According to the most complete scientific research, the APOE gene, which encodes the APOE protein, maybe the key to identifying the likely cause of delayed AD. The development of plaques and tangles, as well as increased amyloid (amyloid-ß) levels and deposition, have been linked to APOE4. Pathogenic mutations in this gene can impact how beta-amyloid deposits and how they are cleared from the body. In this study, we report a novel pathogenic mutation, Arg160Leu, in APOE that was identified in a Moroccan patient. The magnetic resonance imaging of this 67-year-old woman revealed hippocampal shrinkage, and the results of her cognition testing revealed that she is suffering from severe AD. The current study may increase awareness of the genetic risk factors for AD caused by APOE4 mutations.

Unleashing Nature's potential: a computational approach to discovering novel VEGFR-2 inhibitors from African natural compound using virtual screening, ADMET analysis, molecular dynamics, and MMPBSA calculations.

One of the characteristic features of cancer is angiogenesis, the process by which new, aberrant blood vessels are formed from pre-existing blood vessels. The process of angiogenesis begins when VEGF binds to its receptor, the VEGF receptor (VEGFR). The formation of new blood vessels provides nutrients that can promote the growth of cancer cells. When it comes to new blood vessel formation, VEGFR2 is a critical player. Therefore, inhibiting VEGFR2 is an effective way to target angiogenesis in cancer treatment. The aim of our research was to find new VEGFR-2 inhibitors by performing a virtual screening of 13313 from African natural compounds using different in silico techniques. Using molecular docking calculations and ADMET properties, we identified four compounds that exhibited a binding affinity ranging from -11.0 kcal/mol to -11.5 Kcal/mol when bound to VEGFR-2. These four compounds were further analyzed with 100 ns simulations to determine their stability and binding energy using the MM-PBSA method. After comparing the compounds with Regorafenib, a drug approved for anti-angiogenesis treatment, it was found that all the candidates (EANPDB 252, NANPDB 4577, and NANPDB 4580), with the exception of EANPDB 76, could target VEGFR-2 similarly effectively to Regorafenib. Therefore, we recommend three of these agents for anti-angiogenesis treatment because they are likely to deactivate VEGFR-2 and thus inhibit angiogenesis. However, it should be noted that the safety and suitability of these agents for clinical use needs further investigation, as the computer-assisted study did not include in vitro or in vivo experiments.

Multi-combined QSAR, molecular docking, molecular dynamics simulation, and ADMET of Flavonoid derivatives as potent cholinesterase inhibitors.

In searching for a new and efficient therapeutic agent against Alzheimer's disease, a Quantitative structure-activity relationship (QSAR) was derived for 45 Flavonoid derivatives recently synthesized and evaluated as cholinesterase inhibitors. The multiple linear regression method (MLR) was adopted to develop an adequate mathematical model that describes the relationship between a variety of molecular descriptors of the studied compounds and their biological activities (cholinesterase inhibitors). Golbraikh and Tropsha criteria were applied to verify the validity of the built model. The built MLR model was statistically reliable, robust, and predictive (R2 = 0.801, Q2cv = 0.876, R2test = 0.824). Dreiding energy and Molar Refractivity were the major factors that govern the Anti-cholinesterase activity. These results were further exploited to design a new series of Flavonoid derivatives with higher Anti-cholinesterase activities than the existing ones. Thereafter, molecular docking and molecular dynamic studies were performed to predict the binding types of the designed compounds and to investigate their stability at the active site of the Butyrylcholinestérase BuChE protein. The negative and low binding affinity calculated for all designed compounds shows that designed compound 1 has a favorable affinity for the 4TPK. Moreover, molecular dynamics simulation studies confirmed the stability of designed compound 1 in the active pocket of 4TPK over 100 ns. Finally, the ADMET analysis was incorporated to analyze the pharmacokinetics and toxicity parameters. The designed compounds were found to meet the ADMET descriptor criteria at an acceptable level having respectable intestinal permeability and water solubility and can reach the intended destinations.Communicated by Ramaswamy H. Sarma.

In silico design of novel CDK2 inhibitors through QSAR, ADMET, molecular docking and molecular dynamics simulation studies.

The present study aims to investigate about the quantitative structure-activity relationship (QSAR) of a series of Thiazole derivatives reported as anticancer agents (hepatocellular carcinoma), using principally the electronic descriptors calculated by the DFT method and by applying the multiple linear regression method. The developed model showed good statistical parameters (R2 = 0.725, R2adj = 0.653, MSE = 0.060, R2test = 0.827, Q2cv = 0.536). The energy EHOMO orbital, electronic energy (TE), shape coefficient (I), number of rotatable bonds (NROT), and index of refraction (n) were revealed to be the main descriptors influencing the anti-cancer activity. Further, new Thiazole derivatives have been designed and their activities and pharmacokinetic properties have been predicted using the validated QSAR model. The designed molecules were then assessed to molecular docking (MD), and molecular dynamic (MDs) simulation accompanied by the calculation of the binding affinity using MMPBSA script according to 100 ns a simulation trajectory, to study both their affinity and their stability towards CDK2 as a target protein for the cancer disease treatment. This research concluded with the identification of four new CDK2 inhibitors which are A1, A3, A5, and A6 showing good pharmacokinetic properties. The MDs results revealed that the newly designed compound A5 remained stable in the active center of the discovered CDK2 protein, indicating its potential as a novel inhibitor for the treatment of hepatocellular carcinoma. The current findings may eventually contribute to the development of robust CDK2 inhibitors in the future.Communicated by Ramaswamy H. Sarma.

In silico protein engineering shows that novel mutations affecting NAD+ binding sites may improve phosphite dehydrogenase stability and activity.

Pseudomonas stutzeri phosphite dehydrogenase (PTDH) catalyzes the oxidation of phosphite to phosphate in the presence of NAD, resulting in the formation of NADH. The regeneration of NADH by PTDH is greater than any other enzyme due to the substantial change in the free energy of reaction (G°' = - 63.3 kJ/mol). Presently, improving the stability of PTDH is for a great importance to ensure an economically viable reaction process to produce phosphite as a byproduct for agronomic applications. The binding site of NAD+ with PTDH includes thirty-four residues; eight of which have been previously mutated and characterized for their roles in catalysis. In the present study, the unexplored twenty-six key residues involved in the binding of NAD+ were subjected to in silico mutagenesis based on the physicochemical properties of the amino acids. The effects of these mutations on the structure, stability, activity, and interaction of PTDH with NAD+ were investigated using molecular docking, molecular dynamics simulations, free energy calculations, and secondary structure analysis. We identified seven novel mutations, A155I, G157I, L217I, P235A, V262I, I293A, and I293L, that reduce the compactness of the protein while improving PTDH stability and binding to NAD+.

Molecular modeling study of pyrrolidine derivatives as novel myeloid cell leukemia-1 inhibitors through combined 3D-QSAR, molecular docking, ADME/Tox and MD simulation techniques.

A series of pyrrolidine derivatives have been used to study the main structural requirements for designing novel Mcl-1 inhibitors. For this purpose, three models CoMSIA, CoMFA and HQSAR were generated using QSAR molecular modeling techniques. The statistical results of the CoMFA (Q2 = 0.689; R = 0.999; R2pred = 0.986), CoMSIA (Q2 = 0.614; R2 = 0.923; R2pred = 0.815) and HQSAR (Q2= 0.603; R2 = 0.662; R2pred = 0.743) models showed good stability and predictability. The results of the models were presented as contours and colored fragments indicating the favorable and unfavorable contribution to the inhibitory activity of Mcl-1. Based on the obtained results, four new compounds were designed with more potent predicted pIC50 inhibitory activity. The ADME/Tox results and the pharmacokinetic properties revealed that these four compounds are orally bioavailable and show good permeability. In addition the four compounds showing non-inhibitors of CYP3A4 and CYP2D6 with the exception of Pred03. At the level of toxicity profile, the compounds Pred01, Pred02 and Pred03 showed interesting results and showed no AMES toxicity, no hERG inhibition and no skin sensitization. Molecular docking results were used to uncover the mode of interaction between the ligand and key residues of protein binding site. Molecular docking results were supported by molecular simulation and binding free energy estimation (MMPBSA). These results demonstrate the stability of the analyzed compounds in the target protein binding site during a 100 ns trajectory. Finally, all these results create a strong lead to develop promising new Pyrrolidine-based inhibitors against Mcl-1.Communicated by Ramaswamy H. Sarma.

Investigation of the interactions of HSA and SARS-CoV-2 papain-like protease against eugenol for novel COVID-19 drug discovery: spectroscopic and insilico study.

Coronavirus family consist of a member known as SARS-CoV-2, spread drastically in 2019 (Covid-19), affecting millions of people worldwide. Till date there is no clear-clinical therapy or drug, targeted to cure this serious disease. Researches are going on to prevent this corona virus. Here, we tried to explore a novel SARS-CoV-2 papain-like protease as a potential inhibitor. Finally, eugenol was docked with this protease to find prime SARS-inhibitors. In silico studies revealed that eugenol binds to the active site of SARS-CoV-2 papain-like protease with appropriate binding. Moreover, the MD simulation for 100 ns and MMPBSA calculation reveals that eugenol possess potential phytotherapeutic properties against COVID-19. The interaction of eugenol with human serum albumin has been examined by using fluorescence, UV-vis spectroscopy, circular dichroism as well as computational techniques such as molecular docking, molecular dynamic simulation and MMPBSA calculation. Overall investigation shows eugenol having good affinity for HSA Ka 6.80 × 106 M-1.Communicated by Ramaswamy H. Sarma.

Assessment of impacts of industrial effluents on physico-chemical and microbiological qualities of irrigation water of the Fez Rriver, Morocco.

Global water consumption has grown twice as fast as the population. Wastewater is therefore a valuable and renewable source and provides additional water for priority uses. Wastewater can also be a source of pollution; thus, its physico-chemical and biological compositions can present major risks to the environment and human health. The objective of this study was to assess the status of irrigation waters in terms of salinization, accumulation of metallic elements, and microbiological contamination by parasites and pathogenic bacteria. The study focused on the surface water of Oued Fès used for irrigation located downstream of the industrial zone of Doukkarat and upstream of the industrial zone of Ain Noukbi (wastewater) before the confluence with the Oued Sebou, as well as on the treated wastewater of the wastewater treatment plant. The physico-chemical and microbiological analyses were carried out in two periods: summer and winter. Metals were analyzed by ICP-AES. The chemical and bacteriological quality of the wastewater and treated wastewater was found to be poor. These were characterized by organic pollution, including biodegradable pollutants, while upstream the organic residues were not biodegradables. COD, BOD5, Kjeldahl nitrogen, as well as chloride ion (Cl-) are above the standard values. The highest concentrations of Cd, at 850 µg/l, Cu, at 690 µg/l and Mn, at 470 µg/l, largely exceed the international standards and requirements. In addition to fecal contamination, characterized by total coliforms and thermo-tolerant coliforms, other pathogens were present, including helminth eggs, both in the wastewater and in the treated wastewater. Other pathogens, such as Vibrio cholera, were found at all three sites whether in winter or summer, with the exception of the downstream of Oued Fez in winter. As for Salmonella, it was present in treated wastewater during the winter only. The water used for irrigation upstream of Oued Fez and the treated wastewater have poor to very poor quality. Therefore, for a better use of these waters, it is necessary to ensure their regular treatment in order to minimize the impacts on the environment and human health.

High-throughput virtual screening approach of natural compounds as target inhibitors of plasmepsin-II.

Plasmepsin II is a key enzyme in the life cycle of the Plasmodium falciparum parasite responsible for malaria, a disease that is causing deaths on a worldwide scale. Recently, plasmepsin II enzyme has gained much importance as an attractive drug target for the investigation of antimalarial drugs. In this sense, structure-based virtual screening have been utilized as tools in the process of discovering novel natural compounds based on quinoline as potential plasmepsin II inhibitors. Among the 58 quinoline derivatives isolated from different plants was screened by utilizing docking molecular, ADMET approaches, molecular dynamics simulation and MM-PBSA binding free energy. The first step in this work is building the 3 D structures of the plasmepsin II enzyme by using the SWISS-MODEL software. The optimized structures were subjected to virtual screening by Autodock Vina, an entity implicated in PyRx software. 21 were selected based on their binding affinity. The binding modes and interactions of the top-21 selected compounds were evaluated using AutoDock 4.2. Then, the pharmacokinetic proprieties and toxicity of these compounds were evaluated using ADMET analysis. Ten compounds were predicted to have ADMET characteristics with no side effects. Compounds M49 and M53 were found to be potential inhibitors. The stability of the selected two compounds was confirmed by MD simulation and MM/PBSA calculation during 200 ns. This study can be used to predict and to design new antimalarial drugs.Communicated by Ramaswamy H. Sarma.

Structural evolution of Delta lineage of SARS-CoV-2.

One of the main obstacles in prevention and treatment of COVID-19 is the rapid evolution of the SARS-CoV-2 Spike protein. Given that Spike is the main target of common treatments of COVID-19, mutations occurring at this virulent factor can affect the effectiveness of treatments. The B.1.617.2 lineage of SARS-CoV-2, being characterized by many Spike mutations inside and outside of its receptor-binding domain (RBD), shows high infectivity and relative resistance to existing cures. Here, utilizing a wide range of computational biology approaches, such as immunoinformatics, molecular dynamics (MD), analysis of intrinsically disordered regions (IDRs), protein-protein interaction analyses, residue scanning, and free energy calculations, we examine the structural and biological attributes of the B.1.617.2 Spike protein. Furthermore, the antibody design protocol of Rosetta was implemented for evaluation the stability and affinity improvement of the Bamlanivimab (LY-CoV55) antibody, which is not capable of interactions with the B.1.617.2 Spike. We observed that the detected mutations in the Spike of the B1.617.2 variant of concern can cause extensive structural changes compatible with the described variation in immunogenicity, secondary and tertiary structure, oligomerization potency, Furin cleavability, and drug targetability. Compared to the Spike of Wuhan lineage, the B.1.617.2 Spike is more stable and binds to the Angiotensin-converting enzyme 2 (ACE2) with higher affinity.

Assessing the effect of a series of mutations on the dynamic behavior of phosphite dehydrogenase using molecular docking, molecular dynamics and quantum mechanics/molecular mechanics simulations.

Discovered in Pseudomonas stutzeri, phosphite dehydrogenase (PTDH) is an enzyme that catalyzes the oxidation of phosphite to phosphate while simultaneously reducing NAD+ to NADH. Despite several investigations into the mechanism of reaction and cofactor regeneration, only a few studies have focused on improving the activity and stability of PTDH. In this study, we combine molecular docking, molecular dynamics (MD) simulation, and Quantum Mechanics/Molecular Mechanics (QM/MM) to identify the impact of 30 mutations on the activity and stability of PTDH. Molecular docking results suggest that E266Q, K76A, K76M, K76R, K76C, and R237K can act on the NAD+ binding site through relatively weak bond development due to their high free binding energy. Moreover, Mulliken population analysis and potential energy barrier indicate that T101A, E175A, E175A/A176R, A176R, and E266Q act on phosphite oxidation. The mutants M53N, M53A, K76R, D79N, D79A, T101A, W134A, W134F Y139F, A146S, E175A, F198I, F198M, E266Q, H292K, S295A, R301K, and R301A were found to act on the structural dynamic of PTDH. The remaining mutants cause the loss of the nitrogen atom of R237 and H292, respectively, inactivating the enzyme. This study provides specific explanations of how mutations affect weak interactions of PTDH. The results should allow researchers to conduct experimental studies to improve PTDH activity and stability.Communicated by Ramaswamy H. Sarma.

Identification of human immunodeficiency virus -1 E protein-targeting lead compounds by pharmacophore based screening.

OBJECTIVES: To identify potential compounds by seeking the knowledge of molecular interactions between human immunodeficiency virus (HIV) glycoprotein (gp) 120 protein and anti-HIV drug (BMS-488043). METHODS: This study is a computational structure-based drug design study, carried out at University of Taif, Saudi Arabia and African Genome Centre (AGC), Mohammed VI Polytechnic University, Benguerir, Morocco from January 2021 to March 2022. Initially, using the docked structure of gp120 with BMS-488043, a structure-based pharmacophore model was created. The generated model was utilized for virtual screening of the ZINC and ChemBridge database in order to identify hit compounds. To further assess the time-dependent stability of the selected complexes, computer simulation was performed. RESULTS: From pharmacophore-based screening, 356 hits were obtained from both the database. The docking studies of the retrieved hit compounds reveal that all the compounds fit into the binding site of gp120. However, based on the significant interactions with the crucial residues and docking scores four compounds were suggested as potential hits. MD simulation of ChemBridge14695864 and ZINC06893293 in complex with gp120 suggested that both compounds significantly stabilized the receptor. CONCLUSION: These findings could aid in the design of effective drugs against HIV by inhibiting the interaction between gp120 and CD4.

Structural Homology-Based Drug Repurposing Approach for Targeting NSP12 SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2, also known as SARS-CoV-2, is the causative agent of the COVID-19 global pandemic. SARS-CoV-2 has a highly conserved non-structural protein 12 (NSP-12) involved in RNA-dependent RNA polymerase (RdRp) activity. For the identification of potential inhibitors for NSP-12, computational approaches such as the identification of homologous proteins that have been previously targeted by FDA-approved antivirals can be employed. Herein, homologous proteins of NSP-12 were retrieved from Protein DataBank (PDB) and the evolutionary conserved sequence and structure similarity of the active site of the RdRp domain of NSP-12 was characterized. The identified homologous structures of NSP-12 belonged to four viral families: Coronaviridae, Flaviviridae, Picornaviridae, and Caliciviridae, and shared evolutionary conserved relationships. The multiple sequences and structural alignment of homologous structures showed highly conserved amino acid residues that were located at the active site of the RdRp domain of NSP-12. The conserved active site of the RdRp domain of NSP-12 was evaluated for binding affinity with the FDA-approved antivirals, i.e., Sofosbuvir and Dasabuvir in a molecular docking study. The molecular docking of Sofosbuvir and Dasabuvir with the active site that contains conserved motifs (motif A-G) of the RdRp domain of NSP-12 revealed significant binding affinity. Furthermore, MD simulation also inferred the potency of Sofosbuvir and Dasabuvir. In conclusion, targeting the active site of the RdRp domain of NSP-12 with Dasabuvir and Sofosbuvir might reduce viral replication and pathogenicity and could be further studied for the treatment of SARS-CoV-2.