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Schneider-Futschik EK. Chronic Lung and Respiratory Conditions Affecting Lungs and Airways. ACS Pharmacol Transl Sci 2022; 5:692-693. [PMID: 36110373 PMCID: PMC9469184 DOI: 10.1021/acsptsci.2c00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Indexed: 11/30/2022]
Affiliation(s)
- Elena K. Schneider-Futschik
- Cystic Fibrosis Pharmacology Laboratory,
Department of Biochemistry & Pharmacology, Melbourne University, Melbourne, VIC3021, Australia
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2
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Khedri M, Maleki R, Dahri M, Sadeghi MM, Rezvantalab S, Santos HA, Shahbazi MA. Engineering of 2D nanomaterials to trap and kill SARS-CoV-2: a new insight from multi-microsecond atomistic simulations. Drug Deliv Transl Res 2022; 12:1408-1422. [PMID: 34476766 PMCID: PMC8413075 DOI: 10.1007/s13346-021-01054-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/17/2021] [Indexed: 12/23/2022]
Abstract
In late 2019, coronavirus disease 2019 (COVID-19) was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Spike protein is one of the surface proteins of SARS-CoV-2 that is essential for its infectious function. Therefore, it received lots of attention for the preparation of antiviral drugs, vaccines, and diagnostic tools. In the current study, we use computational methods of chemistry and biology to study the interaction between spike protein and its receptor in the body, angiotensin-I-converting enzyme-2 (ACE2). Additionally, the possible interaction of two-dimensional (2D) nanomaterials, including graphene, bismuthene, phosphorene, p-doped graphene, and functionalized p-doped graphene, with spike protein is investigated. The functionalized p-doped graphene nanomaterials were found to interfere with spike protein better than the other tested nanomaterials. In addition, the interaction of the proposed nanomaterials with the main protease (Mpro) of SARS-CoV-2 was studied. Functionalized p-doped graphene nanomaterials showed more capacity to prevent the activity of Mpro. These 2D nanomaterials efficiently reduce the transmissibility and infectivity of SARS-CoV-2 by both the deformation of the spike protein and inhibiting the Mpro. The results suggest the potential use of 2D nanomaterials in a variety of prophylactic approaches, such as masks or surface coatings, and would deserve further studies in the coming years.
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Affiliation(s)
- Mohammad Khedri
- Drug Research Program, Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, 00014, Helsinki, Finland
- Computational Biology and Chemistry Group (CBCG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Reza Maleki
- Computational Biology and Chemistry Group (CBCG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Mohammad Dahri
- Computational Biology and Chemistry Group (CBCG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohammad Moein Sadeghi
- Computational Biology and Chemistry Group (CBCG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sima Rezvantalab
- Renewable Energies Department, Faculty of Chemical Engineering, Urmia University of Technology, 57166-419, Urmia, Iran.
| | - Hélder A Santos
- Drug Research Program, Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, 00014, Helsinki, Finland.
- Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014, Helsinki, Finland.
| | - Mohammad-Ali Shahbazi
- Drug Research Program, Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, 00014, Helsinki, Finland.
- Zanjan Pharmaceutical Nanotechnology Research Center (ZPNRC), Zanjan University of Medical Sciences, 45139-56184, Zanjan, Iran.
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3
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Fornasier E, Macchia ML, Giachin G, Sosic A, Pavan M, Sturlese M, Salata C, Moro S, Gatto B, Bellanda M, Battistutta R. A new inactive conformation of SARS-CoV-2 main protease. ACTA CRYSTALLOGRAPHICA SECTION D STRUCTURAL BIOLOGY 2022; 78:363-378. [PMID: 35234150 PMCID: PMC8900819 DOI: 10.1107/s2059798322000948] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 01/27/2022] [Indexed: 11/26/2022]
Abstract
The SARS‐CoV‐2 main protease (Mpro) has a pivotal role in mediating viral genome replication and transcription of the coronavirus, making it a promising target for drugs against the COVID‐19 pandemic. Here, a crystal structure is presented in which Mpro adopts an inactive state that has never been observed before, called new‐inactive. It is shown that the oxyanion loop, which is involved in substrate recognition and enzymatic activity, adopts a new catalytically incompetent conformation and that many of the key interactions of the active conformation of the enzyme around the active site are lost. Solvation/desolvation energetic contributions play an important role in the transition from the inactive to the active state, with Phe140 moving from an exposed to a buried environment and Asn142 moving from a buried environment to an exposed environment. In new‐inactive Mpro a new cavity is present near the S2′ subsite, and the N‐terminal and C‐terminal tails, as well as the dimeric interface, are perturbed, with partial destabilization of the dimeric assembly. This novel conformation is relevant both for comprehension of the mechanism of action of Mpro within the catalytic cycle and for the successful structure‐based drug design of antiviral drugs.
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4
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Chang Z, Zhan Z, Zhao Z, You Z, Liu Y, Yan Z, Fu Y, Liang W, Zhao L. Application of artificial intelligence in COVID-19 medical area: a systematic review. J Thorac Dis 2021; 13:7034-7053. [PMID: 35070385 PMCID: PMC8743418 DOI: 10.21037/jtd-21-747] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 09/02/2021] [Indexed: 01/08/2023]
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) has caused a large-scale global epidemic, impacting international politics and the economy. At present, there is no particularly effective medicine and treatment plan. Therefore, it is urgent and significant to find new technologies to diagnose early, isolate early, and treat early. Multimodal data drove artificial intelligence (AI) can potentially be the option. During the COVID-19 Pandemic, AI provided cutting-edge applications in disease, medicine, treatment, and target recognition. This paper reviewed the literature on the intersection of AI and medicine to analyze and compare different AI model applications in the COVID-19 Pandemic, evaluate their effectiveness, show their advantages and differences, and introduce the main models and their characteristics. METHODS We searched PubMed, arXiv, medRxiv, and Google Scholar through February 2020 to identify studies on AI applications in the medical areas for the COVID-19 Pandemic. RESULTS We summarize the main AI applications in six areas: (I) epidemiology, (II) diagnosis, (III) progression, (IV) treatment, (V) psychological health impact, and (VI) data security. The ongoing development in AI has significantly improved prediction, contact tracing, screening, diagnosis, treatment, medication, and vaccine development for the COVID-19 Pandemic and reducing human intervention in medical practice. DISCUSSION This paper provides strong advice for using AI-based auxiliary tools for related applications of human diseases. We also discuss the clinicians' role in the further development of AI. They and AI researchers can integrate AI technology with current clinical processes and information systems into applications. In the future, AI personnel and medical workers will further cooperate closely.
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Affiliation(s)
- Zhoulin Chang
- College of Mechanical and Electrical Engineering, Guangdong University of Science and Technology, Dongguan, China
| | - Zhiqing Zhan
- The Third Clinical College, Guangzhou Medical University, Guangzhou, China
| | - Zifan Zhao
- Nanshan College, Guangzhou Medical University, Guangzhou, China
| | - Zhixuan You
- Nanshan College, Guangzhou Medical University, Guangzhou, China
| | - Yang Liu
- School of Information Engineering, Zhengzhou University, Zhengzhou, China
| | - Zhihong Yan
- Kuangji Medical Technology (Guangdong Hengqin) Co., Ltd., Zhuhai, China
| | - Yong Fu
- Kuangji Medical Technology (Guangdong Hengqin) Co., Ltd., Zhuhai, China
| | - Wenhua Liang
- Department of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Lei Zhao
- Department of Physiology, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
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5
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Mahmud S, Hasan MR, Biswas S, Paul GK, Afrose S, Mita MA, Sultana Shimu MS, Promi MM, Hani U, Rahamathulla M, Khan MA, Zaman S, Uddin MS, Rahmatullah M, Jahan R, Alqahtani AM, Saleh MA, Emran TB. Screening of Potent Phytochemical Inhibitors Against SARS-CoV-2 Main Protease: An Integrative Computational Approach. FRONTIERS IN BIOINFORMATICS 2021; 1:717141. [PMID: 36303755 PMCID: PMC9581031 DOI: 10.3389/fbinf.2021.717141] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 09/17/2021] [Indexed: 12/23/2022] Open
Abstract
Coronavirus disease 2019 (COVID-19) is a potentially lethal and devastating disease that has quickly become a public health threat worldwide. Due to its high transmission rate, many countries were forced to implement lockdown protocols, wreaking havoc on the global economy and the medical crisis. The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus for COVID-19, represent an effective target for the development of a new drug/vaccine because it is well-conserved and plays a vital role in viral replication. Mpro inhibition can stop the replication, transcription as well as recombination of SARS-CoV-2 after the infection and thus can halt the formation of virus particles, making Mpro a viable therapeutic target. Here, we constructed a phytochemical dataset based on a rigorous literature review and explored the probability that various phytochemicals will bind with the main protease using a molecular docking approach. The top three hit compounds, medicagol, faradiol, and flavanthrin, had binding scores of −8.3, −8.6, and −8.8 kcal/mol, respectively, in the docking analysis. These three compounds bind to the active groove, consisting of His41, Cys45, Met165, Met49, Gln189, Thr24, and Thr190, resulting in main protease inhibition. Moreover, the multiple descriptors from the molecular dynamics simulation, including the root-mean-square deviation, root-mean-square fluctuation, solvent-accessible surface area, radius of gyration, and hydrogen bond analysis, confirmed the stable nature of the docked complexes. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis confirmed a lack of toxicity or carcinogenicity for the screened compounds. Our computational analysis may contribute toward the design of an effective drug against the main protease of SARS-CoV-2.
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Affiliation(s)
- Shafi Mahmud
- Department of Genetic Engineering and Biotechnology, Microbiology Laboratory, University of Rajshahi, Rajshahi, Bangladesh
| | - Md. Robiul Hasan
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | - Suvro Biswas
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | - Gobindo Kumar Paul
- Department of Genetic Engineering and Biotechnology, Microbiology Laboratory, University of Rajshahi, Rajshahi, Bangladesh
| | - Shamima Afrose
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | - Mohsana Akter Mita
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | | | - Maria Meha Promi
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | - Umme Hani
- Department of Pharmaceutics, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Mohamed Rahamathulla
- Department of Pharmaceutics, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Md. Arif Khan
- Department of Biotechnology and Genetic Engineering, University of Development Alternative, Dhaka, Bangladesh
| | - Shahriar Zaman
- Department of Genetic Engineering and Biotechnology, Microbiology Laboratory, University of Rajshahi, Rajshahi, Bangladesh
| | - Md. Salah Uddin
- Department of Genetic Engineering and Biotechnology, Microbiology Laboratory, University of Rajshahi, Rajshahi, Bangladesh
| | - Mohammed Rahmatullah
- Department of Biotechnology and Genetic Engineering, University of Development Alternative, Dhaka, Bangladesh
| | - Rownak Jahan
- Department of Biotechnology and Genetic Engineering, University of Development Alternative, Dhaka, Bangladesh
| | - Ali M. Alqahtani
- Department of Pharmacology, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Md. Abu Saleh
- Department of Genetic Engineering and Biotechnology, Microbiology Laboratory, University of Rajshahi, Rajshahi, Bangladesh
- *Correspondence: Md. Abu Saleh, ; Talha Bin Emran,
| | - Talha Bin Emran
- Department of Pharmacy, BGC Trust University Bangladesh, Chittagong, Bangladesh
- *Correspondence: Md. Abu Saleh, ; Talha Bin Emran,
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6
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Cho E, Rosa M, Anjum R, Mehmood S, Soban M, Mujtaba M, Bux K, Moin ST, Tanweer M, Dantu S, Pandini A, Yin J, Ma H, Ramanathan A, Islam B, Mey ASJ, Bhowmik D, Haider S. Dynamic Profiling of β-Coronavirus 3CL M pro Protease Ligand-Binding Sites. J Chem Inf Model 2021; 61:3058-3073. [PMID: 34124899 PMCID: PMC8230960 DOI: 10.1021/acs.jcim.1c00449] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Indexed: 01/11/2023]
Abstract
β-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.
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Affiliation(s)
- Eunice Cho
- UCL
School of Pharmacy, London WC1N 1AX, U.K.
| | | | - Ruhi Anjum
- Department
of Biochemistry, Aligarh Muslim University, Aligarh, Uttar Pradesh 202002, India
| | - Saman Mehmood
- Department
of Zoology, Aligarh Muslim University, Aligarh, Uttar Pradesh 202002, India
| | - Mariya Soban
- Department
of Biochemistry, Aligarh Muslim University, Aligarh, Uttar Pradesh 202002, India
| | - Moniza Mujtaba
- Herricks
High School, New Hyde
Park, New York 11040 United States
| | - Khair Bux
- Third
World Center for Science and Technology, H.E.J. Research Institute
of Chemistry, International Centre of Chemical and Biological Sciences, University of Karachi, Karachi 75270 Pakistan
| | - Syed T. Moin
- Third
World Center for Science and Technology, H.E.J. Research Institute
of Chemistry, International Centre of Chemical and Biological Sciences, University of Karachi, Karachi 75270 Pakistan
| | | | - Sarath Dantu
- Department
of Computer Science, Brunel University, Uxbridge UB8 3PH, U.K.
| | - Alessandro Pandini
- Department
of Computer Science, Brunel University, Uxbridge UB8 3PH, U.K.
| | - Junqi Yin
- Center
for Computational Sciences, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Heng Ma
- Data
Science and Learning Division, Argonne National
Laboratory, Lemont, Illinois 60439, United States
| | - Arvind Ramanathan
- Data
Science and Learning Division, Argonne National
Laboratory, Lemont, Illinois 60439, United States
- Consortium
for Advanced Science and Engineering, University
of Chicago, Chicago, Illinois 60637, United
States
| | - Barira Islam
- Department
of Bioscience, University of Huddersfield, Huddersfield HD1 3DH, U.K.
| | - Antonia S. J.
S. Mey
- EaStCHEM
School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K.
| | - Debsindhu Bhowmik
- Computer
Sciences and Engineering Division, Oak Ridge
National Laboratory, Oak Ridge, Tennessee 37830, United States
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7
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Rocha REO, Chaves EJF, Fischer PHC, Costa LSC, Grillo IB, da Cruz LEG, Guedes FC, da Silveira CH, Scotti MT, Camargo AD, Machado KS, Werhli AV, Ferreira RS, Rocha GB, de Lima LHF. A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers. J Biomol Struct Dyn 2021; 40:9214-9234. [PMID: 33970798 PMCID: PMC8127201 DOI: 10.1080/07391102.2021.1924271] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 04/26/2021] [Indexed: 12/14/2022]
Abstract
The main-protease (Mpro) catalyzes a crucial step for the SARS-CoV-2 life cycle. The recent SARS-CoV-2 presents the main protease (MCoV2pro) with 12 mutations compared to SARS-CoV (MCoV1pro). Recent studies point out that these subtle differences lead to mobility variances at the active site loops with functional implications. We use metadynamics simulations and a sort of computational analysis to probe the dynamic, pharmacophoric and catalytic environment differences between the monomers of both enzymes. So, we verify how much intrinsic distinctions are preserved in the functional dimer of MCoV2pro, as well as its implications for ligand accessibility and optimized drug screening. We find a significantly higher accessibility to open binding conformers in the MCoV2pro monomer compared to MCoV1pro. A higher hydration propensity for the MCoV2pro S2 loop with the A46S substitution seems to exercise a key role. Quantum calculations suggest that the wider conformations for MCoV2pro are less catalytically active in the monomer. However, the statistics for contacts involving the N-finger suggest higher maintenance of this activity at the dimer. Docking analyses suggest that the ability to vary the active site width can be important to improve the access of the ligand to the active site in different ways. So, we carry out a multiconformational virtual screening with different ligand bases. The results point to the importance of taking into account the protein conformational multiplicity for new promissors anti MCoV2pro ligands. We hope these results will be useful in prospecting, repurposing and/or designing new anti SARS-CoV-2 drugs.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Rafael E. O. Rocha
- Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Imunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Laboratory of Structural Biology, Department of Molecular Biology, Universität Salzburg, Salzburg, Austria
| | - Elton J. F. Chaves
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Pedro H. C. Fischer
- Laboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
| | - Leon S. C. Costa
- Comp. Modeling Coordination, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Igor Barden Grillo
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Luiz E. G. da Cruz
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Fabiana C. Guedes
- Structural Bioinformatic Laboratory, Institute of Technological Sciences, Universidade Federal de Itajubá, Itabira, Brazil
| | - Carlos H. da Silveira
- Structural Bioinformatic Laboratory, Institute of Technological Sciences, Universidade Federal de Itajubá, Itabira, Brazil
| | - Marcus T. Scotti
- Graduate Program in Natural and Synthetic Bioactive Products; Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Alex D. Camargo
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Karina S. Machado
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Adriano V. Werhli
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Rafaela S. Ferreira
- Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Imunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Gerd B. Rocha
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Leonardo H. F. de Lima
- Laboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
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8
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Pearlstein RA, Wan H, Aravamuthan V. Toward in vivo relevant drug design. Drug Discov Today 2020; 26:637-650. [PMID: 33132106 DOI: 10.1016/j.drudis.2020.10.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 09/16/2020] [Accepted: 10/15/2020] [Indexed: 11/28/2022]
Abstract
Current early and preclinical drug discovery are rooted in decades-old empirical principles describing structure-free energy and structure-function relationships under equilibrium conditions that frequently break down under in vivo conditions. Improved prediction of efficacy and toxicity depends on a paradigm shift to in vivo-relevant principles describing the true nonequilibrium/nonlinear dynamic (NLD) nature of cellular systems. Here, we outline a holistic, in vivo-relevant first principles theory ('Biodynamics'), in which cellular function/dysfunction, and pharmaco-/toxicodynamic effects are considered as emergent behaviors of multimolecular systems powered by covalent and noncovalent free energy sources. The reduction to practice of Biodynamics theory consists of in silico simulations performed at the atomistic and molecular systems levels, versus empirical models fit to in vitro data under the classical paradigm.
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Affiliation(s)
- Robert A Pearlstein
- Novartis Institutes for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA.
| | - Hongbin Wan
- Novartis Institutes for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Vibhas Aravamuthan
- Novartis Institutes for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA 02139, USA
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