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      Explication of Pharmacological Proficiency of Phytoconstituents from Adansonia digitata Bark: An In Vitro and In Silico Approaches

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          Abstract

          Compared to other drug discovery sources, traditional medicine has significantly contributed to developing innovative therapeutic molecules for preventive and curative medicine. The Baobab tree, also known as Adansonia digitata L., is significant in Africa due to its multitude of benefits and various parts that serve different purposes, providing economic support to rural communities. The analysis of a plant sample using Fourier transform infrared (FT-IR) spectroscopy detected multiple functional groups, such as carboxyl and aromatic groups. Additionally, gas chromatography-mass spectroscopy (GC-MS) was utilized to identify various compounds present in the sample, including tetrachloroethylene and octyl ester. The results of different assays, such as α-diphenyl- β-picrylhydrazyl (DPPH), superoxide, nitric oxide scavenging assays, and total antioxidant by thiobarbituric acid method (TBA) and ferric thiocyanate (FTC) method, demonstrated a substantial scavenging of free radicals and an effective antioxidant efficacy. The bark's antimicrobial activity was tested through agar diffusion, resulting in a range of zone of inhibition from 10.1 ± 0.36 mm to 20.85 ± 0.76 mm. The minimum inhibitory concentration (MIC) value was observed to be approximately 0.625  µg/mL. The biofilm inhibition percentage ranged from 9.89% to 57.92%, with the highest percentage being 57.92%. The GC-MS and FT-IR studies revealed phytocompounds, which were then analyzed for their potential therapeutic properties. Computational studies were conducted on the phytocompounds against Pseudomonas aeruginosa and C2 kinase (antioxidant). The study concluded that the Adansonia digitata bark extract and its phytocompound have potential therapeutic efficacy against the target proteins. The best docking scores were about −7.053 kcal/mol and −7.573 kcal/mol for Pseudomonas aeruginosa and C2 kinase (antioxidant), respectively. The interaction patterns with the crucial amino acid residues elucidate the inhibitory efficacy of the phytocompounds.

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          Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes.

          A novel scoring function to estimate protein-ligand binding affinities has been developed and implemented as the Glide 4.0 XP scoring function and docking protocol. In addition to unique water desolvation energy terms, protein-ligand structural motifs leading to enhanced binding affinity are included: (1) hydrophobic enclosure where groups of lipophilic ligand atoms are enclosed on opposite faces by lipophilic protein atoms, (2) neutral-neutral single or correlated hydrogen bonds in a hydrophobically enclosed environment, and (3) five categories of charged-charged hydrogen bonds. The XP scoring function and docking protocol have been developed to reproduce experimental binding affinities for a set of 198 complexes (RMSDs of 2.26 and 1.73 kcal/mol over all and well-docked ligands, respectively) and to yield quality enrichments for a set of fifteen screens of pharmaceutical importance. Enrichment results demonstrate the importance of the novel XP molecular recognition and water scoring in separating active and inactive ligands and avoiding false positives.
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            ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins

            A major problem in structural biology is the recognition of errors in experimental and theoretical models of protein structures. The ProSA program (Protein Structure Analysis) is an established tool which has a large user base and is frequently employed in the refinement and validation of experimental protein structures and in structure prediction and modeling. The analysis of protein structures is generally a difficult and cumbersome exercise. The new service presented here is a straightforward and easy to use extension of the classic ProSA program which exploits the advantages of interactive web-based applications for the display of scores and energy plots that highlight potential problems spotted in protein structures. In particular, the quality scores of a protein are displayed in the context of all known protein structures and problematic parts of a structure are shown and highlighted in a 3D molecule viewer. The service specifically addresses the needs encountered in the validation of protein structures obtained from X-ray analysis, NMR spectroscopy and theoretical calculations. ProSA-web is accessible at https://prosa.services.came.sbg.ac.at
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              ProTox-II: a webserver for the prediction of toxicity of chemicals

              Abstract Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that incorporates molecular similarity, pharmacophores, fragment propensities and machine-learning models for the prediction of various toxicity endpoints; such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways (Tox21) and toxicity targets. The predictive models are built on data from both in vitro assays (e.g. Tox21 assays, Ames bacterial mutation assays, hepG2 cytotoxicity assays, Immunotoxicity assays) and in vivo cases (e.g. carcinogenicity, hepatotoxicity). The models have been validated on independent external sets and have shown strong performance. ProTox-II provides a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite.de/protox_II. The webserver takes a two-dimensional chemical structure as an input and reports the possible toxicity profile of the chemical for 33 models with confidence scores, and an overall toxicity radar chart along with three most similar compounds with known acute toxicity.
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                Author and article information

                Contributors
                Journal
                Scientifica (Cairo)
                Scientifica (Cairo)
                SCIENTIFICA
                Scientifica
                Wiley
                2090-908X
                2024
                16 August 2024
                : 2024
                : 6645824
                Affiliations
                1 deptDepartment of Bioinformatics eduAlagappa University , Karaikudi, Tamil Nadu, India
                2 deptFaculty of Allied Health Sciences deptChettinad Hospital & Research Institute eduChettinad Academy of Research and Education (Deemed to be University) , Kelambakkam, Tamil Nadu, India
                3 deptDepartment of Biotechnology eduAlagappa University , Karaikudi, Tamil Nadu, India
                4 deptCsrDD LAB, Center for Global Health Research deptSaveetha Medical College deptSaveetha Institute of Medical and Technical Sciences , Chennai, Tamil Nadu, India
                5 deptDepartment of Biomedical Science eduAlagappa University , Karaikudi, Tamil Nadu, India
                Author notes

                Academic Editor: Vikram Dalal

                Author information
                https://orcid.org/0000-0002-6452-7632
                https://orcid.org/0000-0002-0531-424X
                https://orcid.org/0000-0002-8954-5220
                https://orcid.org/0000-0002-8115-0486
                https://orcid.org/0000-0002-3154-1331
                Article
                10.1155/2024/6645824
                11343629
                c1f3ecea-24fb-442a-aee7-6b888bad172f
                Copyright © 2024 Sangavi P. et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 August 2023
                : 25 February 2024
                : 30 July 2024
                Funding
                Funded by: DST-FIST
                Award ID: SR/FST/LSI-667/2016(C)
                Funded by: MHRD RUSA 2.0
                Award ID: F.24/51/2014-U
                Funded by: Department of Education Government of India
                Categories
                Research Article

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