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Kumar YB, Kumar N, John L, Mahanta HJ, Vaikundamani S, Nagamani S, Sastry GM, Sastry GN. Analyzing the cation-aromatic interactions in proteins: Cation-aromatic database V2.0. Proteins 2024; 92:179-191. [PMID: 37789571 DOI: 10.1002/prot.26600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/17/2023] [Accepted: 09/07/2023] [Indexed: 10/05/2023]
Abstract
The cation-aromatic database (CAD) is a comprehensive repository of cation-aromatic motifs found in experimentally determined protein structures, first reported in 2007 [Proteins, 2007, 67, 1179]. The present article is an update of CAD that contains information of approximately 27.26 million cation-aromatic motifs. CAD uses three distance parameters (r, d1, and d2) to determine the position of the cation relative to the centroid of the aromatic residue and classifies the motifs as cation-π or cation-σ interactions. As of June 2023, about 193 936 protein structures were retrieved from Protein Data Bank, and this resulted in the identification of an impressive number of 27 255 817 cation-aromatic motifs. Among these motifs, spherical motifs constituted 94.09%, while cylindrical motifs made up the remaining 5.91%. When considering the interaction of metal ions with aromatic residues, 965 564 motifs are identified. Remarkably, 82.08% of these motifs involved the binding of metal ions to the amino acid HIS. Moreover, the analysis of binding preferences between cations and aromatic residues revealed that the HIS-HIS, PHE-ARG, and TRP-ARG pairs exhibited a preferential geometry. The motif pair HIS-HIS was the most prevalent, accounting for 19.87% of the total, closely followed by TYR-LYS at 10.17%. Conversely, the motif pair TRP-HIS had the lowest occurrence, representing only 4.20% of the total. The data generated help in revealing the characteristics and biological functions of cation-aromatic interactions in biological molecules. The updated version of CAD (Cation-Aromatic Database V2.0) can be accessed at https://acds.neist.res.in/cadv2.
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Affiliation(s)
- Y Bhargav Kumar
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Nandan Kumar
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
| | - Lijo John
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
| | - Hridoy Jyoti Mahanta
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - S Vaikundamani
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
| | - Selvaraman Nagamani
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | | | - G Narahari Sastry
- Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
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Durojaye OA, Ejaz U, Uzoeto HO, Fadahunsi AA, Opabunmi AO, Ekpo DE, Sedzro DM, Idris MO. CSC01 shows promise as a potential inhibitor of the oncogenic G13D mutant of KRAS: an in silico approach. Amino Acids 2023; 55:1745-1764. [PMID: 37500789 DOI: 10.1007/s00726-023-03304-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 07/11/2023] [Indexed: 07/29/2023]
Abstract
About 30% of malignant tumors include KRAS mutations, which are frequently required for the development and maintenance of malignancies. KRAS is now a top-priority cancer target as a result. After years of research, it is now understood that the oncogenic KRAS-G12C can be targeted. However, many other forms, such as the G13D mutant, are yet to be addressed. Here, we used a receptor-based pharmacophore modeling technique to generate potential inhibitors of the KRAS-G13D oncogenic mutant. Using a comprehensive virtual screening workflow model, top hits were selected, out of which CSC01 was identified as a promising inhibitor of the oncogenic KRAS mutant (G13D). The stability of CSC01 upon binding the switch II pocket was evaluated through an exhaustive molecular dynamics simulation study. The several post-simulation analyses conducted suggest that CSC01 formed a stable complex with KRAS-G13D. CSC01, through a dynamic protein-ligand interaction profiling analysis, was also shown to maintain strong interactions with the mutated aspartic acid residue throughout the simulation. Although binding free energy analysis through the umbrella sampling approach suggested that the affinity of CSC01 with the switch II pocket of KRAS-G13D is moderate, our DFT analysis showed that the stable interaction of the compound might be facilitated by the existence of favorable molecular electrostatic potentials. Furthermore, based on ADMET predictions, CSC01 demonstrated a satisfactory drug likeness and toxicity profile, making it an exemplary candidate for consideration as a potential KRAS-G13D inhibitor.
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Affiliation(s)
- Olanrewaju Ayodeji Durojaye
- MOE Key Laboratory of Membraneless Organelle and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, 230027, Anhui, China.
- School of Life Sciences, University of Science and Technology of China, Hefei, 230027, Anhui, China.
- Department of Chemical Sciences, Coal City University, Emene, EnuguState, Nigeria.
| | - Umer Ejaz
- MOE Key Laboratory of Membraneless Organelle and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, 230027, Anhui, China
- School of Life Sciences, University of Science and Technology of China, Hefei, 230027, Anhui, China
- School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China
| | - Henrietta Onyinye Uzoeto
- Federal College of Dental Technology, Trans-Ekulu, Enugu State, Nigeria
- Department of Biological Sciences, Coal City University, Emene, Enugu State, Nigeria
| | - Adeola Abraham Fadahunsi
- Graduate School of Biomedical Science and Engineering, University of Maine, Orono, ME, 04469, USA
| | - Adebayo Oluwole Opabunmi
- RNA Medical Center, International Institutes of Medicine, Zhejiang University, Hangzhou, China
- Zhejiang University-University of Edinburgh Institute, Zhejiang University, Hangzhou, China
- The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Daniel Emmanuel Ekpo
- Institute of Biological Science and Technology, National Engineering Research Center for Non-Food Biorefinery, Guangxi Academy of Sciences, Nanning, 530007, China
- Department of Biochemistry, Faculty of Biological Sciences, University of Nigeria, 410001, Nsukka, Enugu State, Nigeria
| | - Divine Mensah Sedzro
- Wisconsin National Primate Research Center, University of Wisconsin Graduate School, 1220 Capitol Court, Madison, 53715, WI, USA.
| | - Mukhtar Oluwaseun Idris
- School of Life Sciences, University of Science and Technology of China, Hefei, 230027, Anhui, China.
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Durojaye OA, Okoro NO, Odiba AS, Nwanguma BC. MasitinibL shows promise as a drug-like analog of masitinib that elicits comparable SARS-Cov-2 3CLpro inhibition with low kinase preference. Sci Rep 2023; 13:6972. [PMID: 37117213 PMCID: PMC10141821 DOI: 10.1038/s41598-023-33024-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 04/06/2023] [Indexed: 04/30/2023] Open
Abstract
SARS-CoV-2 infection has led to several million deaths worldwide and ravaged the economies of many countries. Hence, developing therapeutics against SARS-CoV-2 remains a core priority in the fight against COVID-19. Most of the drugs that have received emergency use authorization for treating SARS-CoV-2 infection exhibit a number of limitations, including side effects and questionable efficacy. This challenge is further compounded by reinfection after vaccination and the high likelihood of mutations, as well as the emergence of viral escape mutants that render SARS-CoV-2 spike glycoprotein-targeting vaccines ineffective. Employing de novo drug synthesis or repurposing to discover broad-spectrum antivirals that target highly conserved pathways within the viral machinery is a focus of current research. In a recent drug repurposing study, masitinib, a clinically safe drug against the human coronavirus OC43 (HCoV-OC43), was identified as an antiviral agent with effective inhibitory activity against the SARS-CoV-2 3CLpro. Masitinib is currently under clinical trial in combination with isoquercetin in hospitalized patients (NCT04622865). Nevertheless, masitinib has kinase-related side effects; hence, the development of masitinib analogs with lower anti-tyrosine kinase activity becomes necessary. In this study, in an attempt to address this limitation, we executed a comprehensive virtual workflow in silico to discover drug-like compounds matching selected pharmacophore features in the SARS-CoV-2 3CLpro-bound state of masitinib. We identified a novel lead compound, "masitinibL", a drug-like analog of masitinib that demonstrated strong inhibitory properties against the SARS-CoV-2 3CLpro. In addition, masitinibL further displayed low selectivity for tyrosine kinases, which strongly suggests that masitinibL is a highly promising therapeutic that is preferable to masitinib.
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Affiliation(s)
- Olanrewaju Ayodeji Durojaye
- MOE Key Laboratory of Membraneless Organelle and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, 230027, Anhui, China
- School of Life Sciences, University of Science and Technology of China, Hefei, 230027, Anhui, China
- Department of Chemical Sciences, Coal City University, Emene, Enugu State, Nigeria
| | - Nkwachukwu Oziamara Okoro
- Department of Pharmaceutical and Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Nigeria, Nsukka, 410001, Nigeria
| | - Arome Solomon Odiba
- Department of Molecular Genetics and Biotechnology, University of Nigeria, Nsukka, 410001, Enugu State, Nigeria.
- Department of Biochemistry, Faculty of Biological Sciences, University of Nigeria, Nsukka, 410001, Enugu State, Nigeria.
| | - Bennett Chima Nwanguma
- Department of Molecular Genetics and Biotechnology, University of Nigeria, Nsukka, 410001, Enugu State, Nigeria.
- Department of Biochemistry, Faculty of Biological Sciences, University of Nigeria, Nsukka, 410001, Enugu State, Nigeria.
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Adedeji EO, Oduselu GO, Ogunlana OO, Fatumo S, Koenig R, Adebiyi E. Anopheles gambiae Trehalase Inhibitors for Malaria Vector Control: A Molecular Docking and Molecular Dynamics Study. INSECTS 2022; 13:1070. [PMID: 36421973 PMCID: PMC9694508 DOI: 10.3390/insects13111070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 10/31/2022] [Accepted: 11/12/2022] [Indexed: 06/07/2023]
Abstract
Trehalase inhibitors are considered safe alternatives for insecticides and fungicides. However, there are no studies testing these compounds on Anopheles gambiae, a major vector of human malaria. This study predicted the three-dimensional structure of Anopheles gambiae trehalase (AgTre) and identified potential inhibitors using molecular docking and molecular dynamics methods. Robetta server, C-I-TASSER, and I-TASSER were used to predict the protein structure, while the structural assessment was carried out using SWISS-MODEL, ERRAT, and VERIFY3D. Molecular docking and screening of 3022 compounds was carried out using AutoDock Vina in PyRx, and MD simulation was carried out using NAMD. The Robetta model outperformed all other models and was used for docking and simulation studies. After a post-screening analysis and ADMET studies, uniflorine, 67837201, 10406567, and Compound 2 were considered the best hits with binding energies of -6.9, -8.9, -9, and -8.4 kcal/mol, respectively, better than validamycin A standard (-5.4 kcal/mol). These four compounds were predicted to have no eco-toxicity, Brenk, or PAINS alerts. Similarly, they were predicted to be non-mutagenic, carcinogenic, or hepatoxic. 67837201, 10406567, and Compound 2 showed excellent stability during simulation. The study highlights uniflorine, 67837201, 10406567, and Compound 2 as good inhibitors of AgTre and possible compounds for malaria vector control.
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Affiliation(s)
- Eunice O. Adedeji
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota 112233, Nigeria
- Department of Biochemistry, College of Science and Technology, Covenant University, Ota 112233, Nigeria
| | - Gbolahan O. Oduselu
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota 112233, Nigeria
- Department of Chemistry, College of Science and Technology, Covenant University, Ota 112233, Nigeria
| | - Olubanke O. Ogunlana
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota 112233, Nigeria
- Department of Biochemistry, College of Science and Technology, Covenant University, Ota 112233, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota 112233, Nigeria
| | - Segun Fatumo
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK
| | - Rainer Koenig
- Institute for Infectious Diseases and Infection Control (IIMK, RG Systemsbiology), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Ezekiel Adebiyi
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota 112233, Nigeria
- Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota 112233, Nigeria
- Department of Computer and Information Sciences, College of Science and Technology, Covenant University, Ota 112233, Nigeria
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), G200, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
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Sedzro DM, Idris MO, Durojaye OA, Yekeen AA, Fadahunsi AA, Alakanse SO. Identifying Potential p53‐MDM2 Interaction Antagonists: An Integrated Approach of Pharmacophore‐Based Virtual Screening, Interaction Fingerprinting, MD Simulation and DFT Studies. ChemistrySelect 2022. [DOI: 10.1002/slct.202202380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Divine Mensah Sedzro
- MOE Key Laboratory of Membraneless Organelle and Cellular Dynamics Hefei National Laboratory for Physical Sciences at the Microscale University of Science and Technology of China Hefei Anhui 230027 China
- School of Life Sciences University of Science and Technology of China Hefei Anhui 230027 China
| | - Mukhtar Oluwaseun Idris
- School of Life Sciences University of Science and Technology of China Hefei Anhui 230027 China
| | - Olanrewaju Ayodeji Durojaye
- MOE Key Laboratory of Membraneless Organelle and Cellular Dynamics Hefei National Laboratory for Physical Sciences at the Microscale University of Science and Technology of China Hefei Anhui 230027 China
- School of Life Sciences University of Science and Technology of China Hefei Anhui 230027 China
- Department of Chemical Sciences Coal City University, Emene Enugu State Nigeria
- ACAII BIOHEALTH LTD, Ikotun Lagos State Nigeria
| | - Abeeb Abiodun Yekeen
- School of Life Sciences University of Science and Technology of China Hefei Anhui 230027 China
| | - Adeola Abraham Fadahunsi
- Graduate School of Biomedical Engineering (GSBSE) University of Maine Orono ME 04469 USA
- Department of Oncology the First Affiliated Hospital of USTC Division of Life Sciences and Medicine University of Science and Technology of China Hefei Anhui 230027 China
- School of Information Science and Technology University of Science and Technology of China Hefei Anhui 230027 China
| | - Suleiman Oluwaseun Alakanse
- School of Life Sciences University of Science and Technology of China Hefei Anhui 230027 China
- Department of Biochemistry Faculty of Life Sciences University of Ilorin Ilorin Kwara State Nigeria
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Wu M, Lv K, Li J, Wu B, He B. Coevolutionary analysis reveals a distal amino acid residue pair affecting the catalytic activity of GH5 processive endoglucanase from Bacillus subtilis BS-5. Biotechnol Bioeng 2022; 119:2105-2114. [PMID: 35438195 DOI: 10.1002/bit.28113] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/05/2022] [Accepted: 04/08/2022] [Indexed: 11/06/2022]
Abstract
EG5C-1, processive endoglucanase from Bacillus subtilis, is a typical bifunctional cellulase with endoglucanase and exoglucanase activities. The engineering of processive endoglucanase focuses on the catalytic pocket or carbohydrate-binding module tailoring based on sequence/structure information. Herein, a computational strategy was applied to identify the desired mutants in the enzyme molecule by evolutionary coupling analysis; subsequently, four residue pairs were selected as evolutionary mutational hotspots. Based on iterative-saturation mutagenesis and subsequent enzymatic activity analysis, a superior mutant K51T/L93T was identified away from the active center. This variant had increased specific activity from 4170 U/µmol of wild-type (WT) to 5678 U/µmol towards CMC-Na and an increase towards the substrate Avicel from 320 U/µmol in WT to 521 U/µmol. In addition, kinetic measurements suggested that superior mutant K51T/L93T had a high substrate affinity (Km ) and a remarkable improvement in catalytic efficiency (kcat /Km ). Furthermore, molecular dynamics simulations revealed that the K51T/L93T mutation altered the spatial conformation at the active site cleft, enhancing the interaction frequency between active site residues and substrate, improving catalytic efficiency and substrate affinity. The current studies provided some perspectives on the effects of distal residue substitution, which might assist in the engineering of processive endoglucanase or other glycoside hydrolases. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Mujunqi Wu
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, 30 Puzhunan road, Nanjing, 211816, Jiangsu, China
| | - Kemin Lv
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, 30 Puzhunan road, Nanjing, 211816, Jiangsu, China
| | - Jiahuang Li
- School of Biopharmacy, China Pharmaceutical University, Nanjing, 211198, Jiangsu, China
| | - Bin Wu
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, 30 Puzhunan road, Nanjing, 211816, Jiangsu, China
| | - Bingfang He
- School of Pharmaceutical Sciences, Nanjing Tech University, 30 Puzhunan road, Nanjing, 211816, Jiangsu, China
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Combined Modeling Study of the Binding Characteristics of Natural Compounds, Derived from Psoralea Fruits, to β-Amyloid Peptide Monomer. Int J Mol Sci 2022; 23:ijms23073546. [PMID: 35408917 PMCID: PMC8998326 DOI: 10.3390/ijms23073546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 03/21/2022] [Accepted: 03/22/2022] [Indexed: 11/16/2022] Open
Abstract
A dysfunctional protein aggregation in the nervous system can lead to several neurodegenerative disorders that result in intracellular inclusions or extracellular aggregates. An early critical event within the pathogenesis of Alzheimer’s disease is the accumulation of amyloid beta peptide within the brain. Natural compounds isolated from Psoralea Fructus (PF) have significant anti-Alzheimer effects as strong inhibitors of Aβ42 aggregation. Computer simulations provide a powerful means of linking experimental findings to nanoscale molecular events. As part of this research four prenylated compounds, the active ingredients of Psoralea Fructus (PF), were studied as Aβ42 accumulation inhibitors using molecular simulations modeling. In order to resolve the binding modes of the ligands and identify the main interactions of Aβ42 residues, we performed a 100 ns molecular dynamics simulation and binding free energy calculations starting from the model of the compounds obtained from the docking study. This study was able to pinpoint the key amino acid residues in the Aβ42 active site and provide useful information that could benefit the development of new Aβ42 accumulation inhibitors.
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