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Männistö PT, Keränen T, Reinikainen KJ, Hanttu A, Pollesello P. The Catechol O-Methyltransferase Inhibitor Entacapone in the Treatment of Parkinson's Disease: Personal Reflections on a First-in-Class Drug Development Programme 40 Years On. Neurol Ther 2024; 13:1039-1054. [PMID: 38809484 PMCID: PMC11263458 DOI: 10.1007/s40120-024-00629-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 05/02/2024] [Indexed: 05/30/2024] Open
Abstract
In the 1980s, Orion Pharma, then a mid-ranking Nordic area pharmaceutical company, established a drug development programme on the inhibition of catechol O-methyltransferase (COMT). This enzyme, which plays an important role in the inactivation of catecholamine neurotransmitters and drugs with a catechol structure, thus came under consideration as a target in the innovative translational and clinical programme we describe in this historical review. The starting point was the conjecture that a peripherally acting COMT inhibitor might improve entry of levodopa into the brain. This had potentially significant implications for the medical treatment of Parkinson's disease (PD). The rationale was that more efficient delivery of levodopa to the brain might allow the high therapeutic doses of levodopa to be reduced and the dose interval to be extended. Elucidation of structure-activity relations paved the way for the discovery and development of entacapone, a 5-nitrocatechol that was a potent and highly specific inhibitor of COMT. Experience in phase III clinical trials established that entacapone, used as an adjunct to regular or controlled-release levodopa preparations (also including a peripherally acting dopa-decarboxylase inhibitor), increased ON-time and reduced OFF-time and improved clinical condition in patients with PD experiencing wearing-off, often with a reduced daily levodopa dose. Several of these studies also identified that entacapone improved patients' quality of life and was cost-effective. Subsequently, entacapone has been amalgamated into a triple-combination preparation (Stalevo®) with levodopa and carbidopa to create a flexible and convenient drug therapy for patients with PD who have end-of-dose motor fluctuations not stabilised on levodopa/dopa-decarboxylase inhibitor treatment. This review offers a historical perspective on a successful programme of drug development by researchers who played central roles in the progress from exploratory hypothesis to registered pharmaceutical product.
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Affiliation(s)
- Pekka T Männistö
- Institute of Pharmacology and Drug Therapy, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Tapani Keränen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Kari J Reinikainen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Anna Hanttu
- Medical Affairs, CNS Branded Products, Orion Pharma, Espoo, Finland
| | - Piero Pollesello
- Content and Communication, Branded Products, Orion Pharma, Orionintie 1, 02101, Espoo, Finland.
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Mayanja R, Kintu C, Diabate O, Soremekun O, Oluwagbemi OO, Wele M, Kalyesubula R, Jjingo D, Chikowore T, Fatumo S. Molecular Dynamic Simulation Reveals Structure Differences in APOL1 Variants and Implication in Pathogenesis of Chronic Kidney Disease. Genes (Basel) 2022; 13:1460. [PMID: 36011371 PMCID: PMC9408642 DOI: 10.3390/genes13081460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/28/2022] [Accepted: 08/08/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND According to observational studies, two polymorphisms in the apolipoprotein L1 (APOL1) gene have been linked to an increased risk of chronic kidney disease (CKD) in Africans. One polymorphism involves the substitution of two amino-acid residues (S342G and I384M; known as G1), while the other involves the deletion of two amino-acid residues in a row (N388 and Y389; termed G2). Despite the strong link between APOL1 polymorphisms and kidney disease, the molecular mechanisms via which these APOL1 mutations influence the onset and progression of CKD remain unknown. METHODS To predict the active site and allosteric site on the APOL1 protein, we used the Computed Atlas of Surface Topography of Proteins (CASTp) and the Protein Allosteric Sites Server (PASSer). Using an extended molecular dynamics simulation, we investigated the characteristic structural perturbations in the 3D structures of APOL1 variants. RESULTS According to CASTp's active site characterization, the topmost predicted site had a surface area of 964.892 Å2 and a pocket volume of 900.792 Å3. For the top three allosteric pockets, the allostery probability was 52.44%, 46.30%, and 38.50%, respectively. The systems reached equilibrium in about 125 ns. From 0-100 ns, there was also significant structural instability. When compared to G1 and G2, the wildtype protein (G0) had overall high stability throughout the simulation. The root-mean-square fluctuation (RMSF) of wildtype and variant protein backbone Cα fluctuations revealed that the Cα of the variants had a large structural fluctuation when compared to the wildtype. CONCLUSION Using a combination of different computational techniques, we identified binding sites within the APOL1 protein that could be an attractive site for potential inhibitors of APOL1. Furthermore, the G1 and G2 mutations reduced the structural stability of APOL1.
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Affiliation(s)
- Richard Mayanja
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe 31405, Uganda
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala 10101, Uganda
| | - Christopher Kintu
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe 31405, Uganda
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala 10101, Uganda
| | - Oudou Diabate
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe 31405, Uganda
- African Center of Excellence in Bioinformatics (ACE-B), University of Science, Technique and Technologies of Bamako (USTTB), Bamako 3206, Mali
| | - Opeyemi Soremekun
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe 31405, Uganda
- Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Durban 4041, South Africa
| | | | - Mamadou Wele
- African Center of Excellence in Bioinformatics (ACE-B), University of Science, Technique and Technologies of Bamako (USTTB), Bamako 3206, Mali
| | - Robert Kalyesubula
- Department of Internal Medicine and Department of Physiology, Makerere University, Kampala 10101, Uganda
| | - Daudi Jjingo
- African Center of Excellence in Bioinformatics (ACE-B), Makerere University, Kampala 10101, Uganda
| | - Tinashe Chikowore
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2050, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe 31405, Uganda
- Department of Non-Communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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Mgoboza C, Okunlola FO, Akawa OB, Aljoundi A, Soliman MES. Talazoparib Dual-targeting on Poly (ADP-ribose) Polymerase-1 and -16 Enzymes Offers a Promising Therapeutic Strategy in Small Cell Lung Cancer Therapy: Insight from Biophysical Computations. Cell Biochem Biophys 2022; 80:495-504. [PMID: 35588345 DOI: 10.1007/s12013-022-01075-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 05/02/2022] [Indexed: 11/27/2022]
Abstract
In recent times, inhibition of poly (ADP-ribose) polymerase (PARP) enzymes by pharmacological drugs has attracted much attention as an anticancer therapy. As reported, PARP-16 has been discovered as a novel anticancer target for small cell lung cancer, and that the inhibition of both PARP-16 and PARP-1 by talazoparib can increase the overall effectiveness of talazoparib in the SCLC treatment. In this study, we employed computational approaches to investigate the differential inhibitory potency of Talazoparib on PARP-1 and PARP-16. Talazoparib has excellent PARP-1 and PARP-16 binding activities, as revealed by the ΔGbind (total binding energy). Pp16-tpb had binding energy of -34.85 kcal/mol, while pp1-tpb had a binding energy of -26.36 kcal/mol. The binding activity of Talazoparib on both PARP-1 and PARP-16 was significantly influenced by van der Waal and electrostatic interactions. Correspondingly, according to the findings of this study, binding residues with total binding energy greater than 1.00 kcal/mol contributed considerably to the Talazoparib's binding activities on PARP-1 and PARP-16. We believe the findings of this study will pave the way for developing dual targeting of PARP enzymes as a strategy for small-cell lung cancer treatment.
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Affiliation(s)
- Chwayita Mgoboza
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa
| | - Felix O Okunlola
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa
| | - Oluwole B Akawa
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa
| | - Aimen Aljoundi
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa
| | - Mahmoud E S Soliman
- Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa.
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