Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors.

Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunities to accelerate and improve the process of discovering and developing new drugs. The use of AI in drug discovery is still in its early stages, but it has the potential to revolutionize the way new drugs are discovered and developed. As AI technology continues to evolve, it is likely that AI will play an even greater role in the future of drug discovery. AI is used to identify new drug targets, design new molecules, and predict the efficacy and safety of potential drugs. The inclusion of AI in drug discovery can screen millions of compounds in a matter of hours, identifying potential drug candidates that would have taken years to find using traditional methods. AI is highly utilized in the pharmaceutical industry by optimizing processes, reducing waste, and ensuring quality control. This review covers much-needed topics, including the different types of machine-learning techniques, their applications in drug discovery, and the challenges and limitations of using machine learning in this field. The state-of-the-art of AI-assisted pharmaceutical discovery is described, covering applications in structure and ligand-based virtual screening, de novo drug creation, prediction of physicochemical and pharmacokinetic properties, drug repurposing, and related topics. Finally, many obstacles and limits of present approaches are outlined, with an eye on potential future avenues for AI-assisted drug discovery and design.

Toxicological study on ibuprofen and selenium in freshwater mussel Lamellidens marginalis and exploring the microbial cytochrome through modelling and quantum mechanics approaches for its toxicity degradation in contaminated environment.

Toxicological stress in aquatic organisms is caused by the discharge of hundreds of toxic pollutants and contaminants among which the current study concentrates on the toxic effect of non-steroidal anti-inflammatory drug ibuprofen (IBF) and the trace element selenium (Se). In this study, IBF and Se toxicity on freshwater mussel Lamellidens marginalis was studied for 14 days, and in silico predictions for their degradation were made using Molecular modelling and Quantum Mechanical approaches. The degrading propensity of cytochrome c oxidase proteins from Trametes verticillatus and Thauera selenatis (Turkey tail fungi and Gram-negative bacteria) is examined into atom level. The results of molecular modelling study indicate that ionic interactions occur in the T. selenatis-HEME bound complex by Se interacting directly with HEME, and in the T. versicolor-HEME bound complex by IBF bound to a nearby region of HEME. Experimental and theoretical findings suggest that, the toxicological effects of Se and IBF pollution can be reduced by bioremediation with special emphasis on T. versicolor, and T. selenatis, which can effectively interact with Se and IBF present in the environment and degrade them. Besides, this is the first time in freshwater mussel L. marginalis that ibuprofen and selenium toxicity have been studied utilizing both experimental and computational methodologies for their bioremediation study.

Multivariate Data Analysis Assisted Mining of Nutri-rich Genotypes from North Eastern Himalayan Germplasm Collection of Perilla (Perilla frutescens L.).

Understanding the nutritional diversity in Perilla (Perilla frutescens L.) is essential for selecting and developing superior varieties with enhanced nutritional profiles in the North Eastern Himalayan (NEH) region of India. In this study, we assessed the nutritional composition of 45 diverse perilla germplasm collected from five NEH states using standard protocols and advanced analytical techniques. Significant variability was observed in moisture (0.39-11.67%), ash (2.59-7.13%), oil (28.65-74.20%), protein (11.05-23.15%), total soluble sugars (0.34-3.67%), starch (0.01-0.55%), phenols (0.03-0.87%), ferric reducing antioxidant power (0.45-1.36%), palmitic acid (7.06-10.75%), stearic acid (1.96-2.29%), oleic acid (8.11-13.31%), linoleic acid (15.18-22.74%), and linolenic acid (55.47-67.07%). Similarly, significant variability in mineral content (ppm) was also observed for aluminium, calcium, cobalt, chromium, copper, iron, potassium, magnesium, manganese, molybdenum, sodium, nickel, phosphorus, and zinc. Multivariate analyses, including hierarchical clustering analysis (HCA) and principal component analysis (PCA), revealed the enriched nutritional diversity within the germplasm. Correlation analysis indicated significant positive and negative relationships between nutritional parameters, indicating potential biochemical and metabolic interactions present in the perilla seeds. TOPSIS-based ranking identified promising genotypes for functional foods, pharmaceuticals, and nutritional applications. This study provides a first in-depth report of the nutritional composition and diversity of perilla germplasm in the NEH region, thus aiding in the identification of superior varieties for food and nutritional diversification and security.

Molecular interaction analysis of ß-1, 3 glucan binding protein with Bacillus licheniformis and evaluation of its immunostimulant property in Oreochromis mossambicus.

Analyzing the health benefits of any two immunostimulants (synbiotics) in combined form and information on their interactions gain more visibility in the usage of synbiotics in aquafarms. With this intention, the current work explores the immunostimulant effect and structural interaction of synbiotic (ß-1, 3 glucan binding protein from marine crab, Portunus pelagicus (Ppß-GBP) and Bacillus licheniformis) on Oreochromis mossambicus. The experimental diet was prepared with Ppß-GBP and B. licheniformis, and nourished to the fingerlings of O. mossambicus for 30 days. After the experimental trial, a higher growth rate and immune reactions (lysozyme, protease, myeloperoxidase and alkaline phosphatase activity) were noticed in the fish nourished with synbiotic (B. licheniformis and Ppß-GBP) enriched diet. Moreover, the synbiotic enriched diet elevated the antioxidant responses like glutathione peroxidase (GSH-Px) and catalase (CAT) activity in the experimental diet-nurtured fish. At the end of the feed trial, synbiotic diet nourished fish shows an increased survival rate during Aeromonas hydrophila infection, reflecting the disease resistance potential of experimental fish. Also, the interaction between Ppß-GBP and Bacillus licheniformis was analyzed through computational approaches. The results evidenced that, Ppß-GBP interacts with the B. licheniformis through sugar-based ligand, ß-glucan through a hydrogen bond with a good docking score. Thus, the synbiotic diet would be an effective immunostimulant to strengthen the fish immune system for better productivity.

Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries.

The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecules to overcome any disease is a costly and lengthy process, but the process continues uninterrupted. The critical point to consider the drug design is to use the available data resources and to find new and novel leads. Once the drug target is identified, several interdisciplinary areas work together with artificial intelligence (AI) and machine learning (ML) methods to get enriched drugs. These AI and ML methods are applied in every step of the computer-aided drug design, and integrating these AI and ML methods results in a high success rate of hit compounds. In addition, this AI and ML integration with high-dimension data and its powerful capacity have taken a step forward. Clinical trials output prediction through the AI/ML integrated models could further decrease the clinical trials cost by also improving the success rate. Through this review, we discuss the backend of AI and ML methods in supporting the computer-aided drug design, along with its challenge and opportunity for the pharmaceutical industry. From the available information or data, the AI and ML based prediction for the high throughput virtual screening. After this integration of AI and ML, the success rate of hit identification has gained a momentum with huge success by providing novel drugs.

Firecracker Maxillofacial Injury in a 6-Year-Old Child- A Case Report.

The present case report highlights the management of a 6 years old female child who suffered oral and maxillofacial injury due to explosion of a fire cracker inside the mouth which was managed by primary closure after complete debridement and to prevent the post treatment microstomia, a modified microstomia prevention intraoral prosthetic appliance was given and followed up for 15 months.

Replantation of a Iatrogenically Avulsed Mandibular Premolar Undergoing Orthodontic Therapy: A 5 Year Follow-Up.

The succedaneous permanent teeth develop in close proximity to primary teeth. They can get accidentally luxated or avulsed during the extraction of primary teeth. The purpose of this paper was to describe a case of a 14-year-old boy with an "iatrogenic avulsion" of an immature mandibular second premolar during the extraction of a primary mandibular second molar. The case was managed successfully with replantation technique within 30 minutes of extra oral period and followed up for 5 years. The replanted tooth remained clinically asymptomatic, showed continued root development and eruption and remained vital. This paper had also discussed about the modifications in extraction technique to avoid the iatrogenic avulsion of permanent tooth bud during extraction of primary teeth.

Structure-Based Virtual Screening Reveals Ibrutinib and Zanubrutinib as Potential Repurposed Drugs against COVID-19.

Coronavirus disease (COVID)-19 is the leading global health threat to date caused by a severe acute respiratory syndrome coronavirus (SARS-CoV-2). Recent clinical trials reported that the use of Bruton's tyrosine kinase (BTK) inhibitors to treat COVID-19 patients could reduce dyspnea and hypoxia, thromboinflammation, hypercoagulability and improve oxygenation. However, the mechanism of action remains unclear. Thus, this study employs structure-based virtual screening (SBVS) to repurpose BTK inhibitors acalabrutinib, dasatinib, evobrutinib, fostamatinib, ibrutinib, inositol 1,3,4,5-tetrakisphosphate, spebrutinib, XL418 and zanubrutinib against SARS-CoV-2. Molecular docking is conducted with BTK inhibitors against structural and nonstructural proteins of SARS-CoV-2 and host targets (ACE2, TMPRSS2 and BTK). Molecular mechanics-generalized Born surface area (MM/GBSA) calculations and molecular dynamics (MD) simulations are then carried out on the selected complexes with high binding energy. Ibrutinib and zanubrutinib are found to be the most potent of the drugs screened based on the results of computational studies. Results further show that ibrutinib and zanubrutinib could exploit different mechanisms at the viral entry and replication stage and could be repurposed as potential inhibitors of SARS-CoV-2 pathogenesis.

An in silico pharmacological approach toward the discovery of potent inhibitors to combat drug resistance HIV-1 protease variants.

Protease inhibitors (PIs) are crucial drugs in highly active antiretroviral therapy for human immunodeficiency virus-1 (HIV-1) infections. However, resistance owing to mutations challenge the long-term efficacy in the medication of HIV-1-infected individuals. Lopinavir (LPV) and darunavir (DRV), two second-generation drugs are the most potent among PIs, hustling the drug resistance when mutations occur in the active and nonactive site of the protease (PR). Herein, we strive for compounds that can stifle the function of wild-type (WT) HIV-1 PR along with four major single mutants (I54M, V82T, I84V, and L90M) instigating resistance to the PIs using in silico approach. Six common compounds are retrieved from six databases using combined pharmacophore-based and structure-based virtual screening methodology. LPV and DRV are docked and the binding free energy is calculated to set the cut-off value for selecting compounds. Further, to gain insight into the stability of the complexes the molecular dynamics simulation (MDS) is carried out, which uncovers two lead molecules namely NCI-524545 and ZINC12866729. Both the lead molecules connect with WT and mutant HIV-1 PRs through strong and stable hydrogen bond interactions when compared with LPV and DRV throughout the trajectory analysis. Interestingly, NCI-524545 and ZINC12866729 exhibit direct interactions with I50/50' by replacing the conserved water molecule as evidenced by MDS, which indicates the credible potency of these compounds. Hence, we concluded that NCI-524545 and ZINC12866729 have great puissant to restrain the role of drug resistance HIV-1 PR variants, which can also show better activity through in vivo and in vitro conditions.

α-bisabolol ß-D-fucopyranoside as a potential modulator of ß-amyloid peptide induced neurotoxicity: An in vitro &in silico study.

Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder affecting the elderly people. For the AD treatment, there is inefficiency in the existing medication, as these drugs reduce only the symptoms of the disease. Since multiple pathological proteins are involved in the development of AD, searching for a single molecule targeting multiple AD proteins will be a new strategy for the management of AD. In view of this, the present study was designed to synthesize and evaluate the multifunctional neuroprotective ability of the sesquiterpene glycoside α-bisabolol ß-D-fucopyranoside (ABFP) against multiple targets like acetylcholinesterase, oxidative stress and ß-amyloid peptide aggregation induced cytotoxicity. In silico computational docking and simulation studies of ABFP with acetylcholinesterase (AChE) showed that it can interact with Asp74 and Thr75 residues of the enzyme. The in vitro studies showed that the compound possess significant ability to inhibit the AChE enzyme apart from exhibiting antioxidant, anti-aggregation and disaggregation properties. In addition, molecular dynamics simulation studies proved that the interacting residue between Aß peptide and ABFP was found to be involved in Leu34 and Ile31. Furthermore, the compound was able to protect the Neuro2 a cells against Aß25-35 peptide induced toxicity. Overall, the present study evidently proved ABFP as a neuroprotective agent, which might act as a multi-target compound for the treatment of Alzheimer's disease.

Cdk5: A main culprit in neurodegeneration.

Objectives: Neurodegenerative diseases (NDs) such as Alzheimer Diseases (AD), Parkinson Diseases (PD) are a huge public health problem. The elucidation of their pathophysiological mechanism is one of our greatest challenges. Hyperactive immune system contributes to the pathophysiology of neurological disorders. Methods: In this review article, we have highlighted the neurodegenerative role of CDK5 and its involvement in Amyloid precursor pathway via Beta secretase enzyme. Results:All the landmark research reports for CDK5 were considered for this review and its involvement in disrupted autophagy and hyper immune response is the key cause for neurodegeneration. Conclusion: In conclusion, the present review focus on the pathways associated with Cdk5 and its role in causing neurodegeneration.

Atom-based 3D-QSAR, induced fit docking, and molecular dynamics simulations study of thieno[2,3-b]pyridines negative allosteric modulators of mGluR5.

Atom-based three dimensional-quantitative structure-activity relationship (3D-QSAR) model was developed on the basis of 5-point pharmacophore hypothesis (AARRR) with two hydrogen bond acceptors (A) and three aromatic rings for the derivatives of thieno[2,3-b]pyridine, which modulates the activity to inhibit the mGluR5 receptor. Generation of a highly predictive 3D-QSAR model was performed using the alignment of predicted pharmacophore hypothesis for the training set (R2 = 0.84, SD = 0.26, F = 45.8, N = 29) and test set (Q2 = 0.74, RMSE = 0.235, Pearson-R = 0.94, N = 9). The best pharmacophore hypothesis AARRR was selected, and developed three dimensional-quantitative structure activity relationship (3D-QSAR) model also supported the outcome of this study by means of favorable and unfavorable electron withdrawing group and hydrophobic regions of most active compound 42d and least active compound 18b. Following, induced fit docking and binding free energy calculations reveals the reliable binding orientation of the compounds. Finally, molecular dynamics simulations for 100 ns were performed to depict the protein-ligand stability. We anticipate that the resulted outcome could be supportive to discover potent negative allosteric modulators for metabotropic glutamate receptor 5 (mGluR5).

Dihydroactinidiolide, a natural product against Aß25-35 induced toxicity in Neuro2a cells: Synthesis, in silico and in vitro studies.

Synthesis of natural products has speeded up drug discovery process by minimizing the time for their purification from natural source. Several diseases like Alzheimer's disease (AD) demand exploring multi targeted drug candidates, and for the first time we report the multi AD target inhibitory potential of synthesized dihydroactinidiolide (DA). Though the activity of DA in several solvent extracts have been proved to possess free radical scavenging, anti bacterial and anti cancer activities, its neuroprotective efficacy has not been evidenced yet. Hence DA was successfully synthesized from ß-ionone using facile two-step oxidation method. It showed potent acetylcholinesterase (AChE) inhibition with half maximal inhibitory concentration (IC50) 34.03 nM, which was further supported by molecular docking results showing strong H bonding with some of the active site residues such as GLY117, GLY119 and SER200 of AChE. Further it displayed DPPH and (.NO) scavenging activity with IC50 value 50 nM and metal chelating activity with IC50 >270 nM. Besides, it significantly prevented amyloid ß25-35 self-aggregation and promoted its disaggregation at 270 nM. It did not show cytotoxic effect towards Neuro2a (N2a) cells up to 24 h at 50 and 270 nM while it significantly increased viability of amyloid ß25-35 treated N2a cells through ROS generation at both the concentrations. Cytotoxicity profile of DA against human PBMC was quite impressive. Hemolysis studies also revealed very low hemolysis i.e. minimum 2.35 to maximum 5.61%. It also had suitable ADME properties which proved its druglikeness. The current findings demand for further in vitro and in vivo studies to develop DA as a multi target lead against AD.

In vitro and in silico studies on cell adhesion protein peroxinectin from Fenneropenaeus indicus and screening of heme blockers against activity.

In invertebrates, the prophenoloxidase (proPO) pathway is involved in the phenol-like antioxidant production against invading pathogens. Overproduction of melanin and phenolic substances leads to the disruption of hemocytes (own host cells); therefore, there is a prerequisite to regulate the antioxidant production, which is performed by the proteases and proPO-associated cell adhesion protein peroxinectin (PX). PX is a macromolecular structure consisting of protein involved in the proPO pathway, which is a potential target in the regulatory mechanism in crustaceans. In the proPO cascade, pattern recognition proteins initiate the proPO cascade by the consequent reaction, and PX is involved in the key step in the regulatory mechanism of phenoloxidase enzyme synthesis. In the present study, Indian white shrimp Fenneropenaeus indicus PX (Fein-PX) gene sequence was used. Upregulation of Fein-PX was determined using immunostimulants ß-glucan (agonists) and examined its expression by quantitative RT-PCR. To find the downregulation or negative regulation of Fein-PX, inhibitors were screened, and its 3D model provides molecular insights into the rationale inhibitor design for developing an effective molecule against Fein-PX.

Understanding the importance of conservative hypothetical protein LdBPK_070020 in Leishmania donovani and its role in subsistence of the parasite.

The genome of Leishmania donovani, the causative agent of visceral leishmaniasis, codes for approximately 65% of both conserved and non-conserved hypothetical proteins. Studies on 'conserved hypothetical' proteins are expected to reveal not only new and crucial aspects of Leishmania biochemistry, but it could also lead to discovery of novel drug candidates. Conserved hypothetical protein, LdBPK_070020, is a 31.14 kDa protein, encoded by an 810 bp gene. BLAST analysis of LdBPK_070020, performed against NCBI non-redundant database, showed 80-99% similarity with conserved hypothetical proteins of Leishmania belonging to other species. Using homologues recombination method, we have performed gene knockout of LdBPK_070020 and effects of the same were investigated on the parasite. The gene knocked out strain shows significant retardation in growth with respect to wild type. Detailed biochemical studies indicated towards important role of LdBPK_070020 in the parasite survival and growth.

Modeling of macromolecular proteins in prophenoloxidase cascade through experimental and computational approaches.

Prophenoloxidase (ProPO) cascade is a principal defense system in crustaceans, which consists of a variety of pattern recognition proteins (lipopolysaccharide and ß-glucan-binding protein [ß-GBP], ß-GBP, and ß-glucan recognition protein), proteases (serine protease), and protease inhibitors (α2-macroglobulin and pacifastin) to regulate the protection mechanism in crustaceans. In the prophneoloxidase pathway, the protein-protein interactions (PPIs) and other immune-related analyses still have not been reported. Moreover, the structural features of ProPO cascade proteins have not yet been reported, hence we constructed the three-dimensional structural features for all ProPO pathway proteins. Their PPIs were studied through an in silico approach. Laminarin has been identified as a triggering activator and it showed energetic binding with homology modeled ß-GBP and activated the ß-GBP, followed by the protein-protein complex formation leading to phenoloxidase synthesis. These findings provided a novel view of the ProPO mechanism and enhanced our knowledge of the innate immune system in crustaceans via computation. In conclusion, we propose a combined experimental and computational approach to analyze the mechanism of ProPO cascade proteins.

Assessment of dual inhibition property of newly discovered inhibitors against PCAF and GCN5 through in silico screening, molecular dynamics simulation and DFT approach.

p300/CBP-associated factor (PCAF) is one among the histone acetyltransferase (HAT) family enzymes. It is involved in the regulation of transcription by modifying the chromatin structure indirectly through the acetylation of histones. It has been emerged as a promising drug target for various types of cancer. A four-point pharmacophore with two hydrogen bond acceptor, one aromatic ring and one hydrophobic feature, was generated for six highly active isothiazolone derivatives as PCAF inhibitors in order to elucidate their anticancer activity. The generated pharmacophore was used for screening three different databases such as Maybridge, Life Chemicals and Chembridge databases. The screened compounds were further filtered through docking studies. Then the compounds were further carried for ADME prediction. The best three compounds BTB09406, F1418-0051 and F1880-1727 were docked to GCN5 to explore the dual inhibitory properties. The conformational stability of the protein-ligand complexes were analyzed through molecular dynamics simulation. Three best compounds were finally went through electronic structure analysis using density functional theory (DFT) at B3LYP/6-31**G level to understand their molecular reactivity. The results obtained from this study exploit that the three best compounds (BTB09406, F1418-0051 and F1880-1727) were found to have more potent and dual inhibitory properties.

Structure-Based Virtual Screening and Biological Evaluation of a Calpain Inhibitor for Prevention of Selenite-Induced Cataractogenesis in an in Vitro System.

Calpains belong to the family of calcium-dependent, structurally related intracellular cysteine proteases that exhibit significant functions in evolution of different types of cataracts in human as well as animal models. Application of calpain inhibitors generated through a virtual screening workflow may provide new avenues for the prevention of cataractogenesis. Hence, in the current study, compounds were first screened for potent calpain inhibitory activity by employing a structure-based approach, and the screening results were then validated through biological experiments in rat lenses. A hit compound, HTS08688, was obtained by structure-based virtual screening. A micromolar concentration of HTS08688 was found to prevent in vitro cataractogenesis in isolated Wistar rat lenses, while maintaining the antioxidant and calcium concentrations at near normal levels. Inhibition of superoxide anion generation, as observed through cytochemical localization studies, and maintenance of structural integrity, as demonstrated by histological analysis of lenticular tissue, also suggested that HTS08688 can ameliorate the cataractous condition induced by selenite in an in vitro rodent model. A cell proliferation assay was performed; the IC 50 value of the screened calpain inhibitor, HTS08688, against human lenticular epithelial cells-b3 was found to be 177 µM/mL. This combined theoretical and experimental approach has demonstrated a potent lead compound, HTS08688, that exhibits putative anticataractogenic activity by virtue of its potential to inhibit calpain.

Molecular cloning, relative expression, and structural analysis of pattern recognition molecule ß-glucan binding protein from mangrove crab Episesarma tetragonum.

A full-length cDNA of a ß-glucan binding protein (ß-GBP) gene was identified from the mangrove crab Episesarma tetragonum. The open reading frame of the E. tetragonum ß-GBP (Epte ß-GBP) is 1,167 bp long, encoding a polypeptide of 389 amino acids. The deduced amino acid sequence of Epte ß-GBP gene has conserved a potential recognition motif for ß-1,3 linkages of polysaccharides and putative RGD (Arg-Gly-Asp) cell adhesion sites. Phylogenetic analysis of the Epte ß-GBP gene showed the similarity with ß-GBPs of other crustaceans and arthropods. Quantitative RT-PCR results showed the upregulation of Epte ß-GBP gene expression in E. tetragonum hemocytes following a 12-H challenge in response to ß-glucan (ß-G). Epte ß-GBP was involved in the regulation and activation of the prophenoloxidase cascade. A three-dimensional structure of active Epte ß-GBP was modeled by homology modeling and refined with molecular dynamics simulations. A structural aspect of the protein is discussed based on experimental and theoretical results obtained.

Molecular insights on analogs of HIV PR inhibitors toward HTLV-1 PR through QM/MM interactions and molecular dynamics studies: comparative structure analysis of wild and mutant HTLV-1 PR.

Retroviruses HTLV-1 and HIV-1 are the primary causative agents of fatal adult T-cell leukemia and acquired immune deficiency syndrome (AIDS) disease. Both retroviruses are similar in characteristics mechanism, and it encodes for protease that mainly involved in the viral replication process. On the basis of the therapeutic success of HIV-1 PR inhibitors, the protease of HTLV-1 is mainly considered as a potential target for chemotherapy. At the same time, structural similarities in both enzymes that originate HIV PR inhibitors can also be an HTLV-1 PR inhibitor. But the expectations failed because of rejection of HIV PR inhibitors from the HTLV-1 PR binding pocket. In this present study, the reason for the HIV PR inhibitor rejection from the HTLV-1 binding site was identified through sequence analysis and molecular dynamics simulation method. Functional analysis of M37A mutation in HTLV PR clearly shows that the MET37 specificity and screening of potential inhibitors targeting MET37 is performed by using approved 90% similar HIV PR inhibitor compounds. From this approach, we report few compounds with a tendency to accept/donate electron specifically to an important site residue MET37 in HTLV-1 PR binding pocket.