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International Journal of Molecular... Apr 2021All molecular systems, from small molecules to macromolecules, exhibit specific characteristics for a specific environment and time. In order to gain an accurate...
All molecular systems, from small molecules to macromolecules, exhibit specific characteristics for a specific environment and time. In order to gain an accurate understanding of the functions of all types of molecules, studies of their structure and dynamics are essential. Through dynamic studies, using techniques such as spectroscopy, structure determination, and computer analysis, it is possible to collect functional information on molecules at specific times and in specific environments. Such information not only reveals the properties and mechanisms of action of molecules but also provides insights that can be applied to various industries, such as the development of new materials and drugs. Herein, I discuss the importance of molecular dynamics studies, present the time scale of molecular motion, and review techniques for analyzing molecular dynamics.
Topics: Macromolecular Substances; Molecular Dynamics Simulation
PubMed: 33916359
DOI: 10.3390/ijms22073761 -
Biochemical Society Transactions Aug 2020Proteins are dynamic molecules that can transition between a potentially wide range of structures comprising their conformational ensemble. The nature of these... (Review)
Review
Proteins are dynamic molecules that can transition between a potentially wide range of structures comprising their conformational ensemble. The nature of these conformations and their relative probabilities are described by a high-dimensional free energy landscape. While computer simulation techniques such as molecular dynamics simulations allow characterisation of the metastable conformational states and the transitions between them, and thus free energy landscapes, to be characterised, the barriers between states can be high, precluding efficient sampling without substantial computational resources. Over the past decades, a dizzying array of methods have emerged for enhancing conformational sampling, and for projecting the free energy landscape onto a reduced set of dimensions that allow conformational states to be distinguished, known as collective variables (CVs), along which sampling may be directed. Here, a brief description of what biomolecular simulation entails is followed by a more detailed exposition of the nature of CVs and methods for determining these, and, lastly, an overview of the myriad different approaches for enhancing conformational sampling, most of which rely upon CVs, including new advances in both CV determination and conformational sampling due to machine learning.
Topics: Computational Biology; Molecular Dynamics Simulation; Protein Conformation; Proteins
PubMed: 32756904
DOI: 10.1042/BST20200193 -
Molecules (Basel, Switzerland) Oct 2020The prototypical model for NOD-like receptor (NLR) inflammasome assembly includes nucleotide-dependent activation of the NLR downstream of pathogen- or danger-associated... (Review)
Review
The prototypical model for NOD-like receptor (NLR) inflammasome assembly includes nucleotide-dependent activation of the NLR downstream of pathogen- or danger-associated molecular pattern (PAMP or DAMP) recognition, followed by nucleation of hetero-oligomeric platforms that lie upstream of inflammatory responses associated with innate immunity. As members of the STAND ATPases, the NLRs are generally thought to share a similar model of ATP-dependent activation and effect. However, recent observations have challenged this paradigm to reveal novel and complex biochemical processes to discern NLRs from other STAND proteins. In this review, we highlight past findings that identify the regulatory importance of conserved ATP-binding and hydrolysis motifs within the nucleotide-binding NACHT domain of NLRs and explore recent breakthroughs that generate connections between NLR protein structure and function. Indeed, newly deposited NLR structures for NLRC4 and NLRP3 have provided unique perspectives on the ATP-dependency of inflammasome activation. Novel molecular dynamic simulations of NLRP3 examined the active site of ADP- and ATP-bound models. The findings support distinctions in nucleotide-binding domain topology with occupancy of ATP or ADP that are in turn disseminated on to the global protein structure. Ultimately, studies continue to reveal how the ATP-binding and hydrolysis properties of NACHT domains in different NLRs integrate with signaling modules and binding partners to control innate immune responses at the molecular level.
Topics: Adenosine Triphosphate; Animals; Calcium-Binding Proteins; Humans; Hydrolysis; Inflammasomes; Molecular Dynamics Simulation; NLR Family, Pyrin Domain-Containing 3 Protein
PubMed: 33036374
DOI: 10.3390/molecules25194572 -
British Journal of Pharmacology Jul 2022Hirudin variants are the most powerful thrombin inhibitors discovered to date, with a lower risk of bleeding than heparin. For anticoagulation, the C-termini of hirudin...
BACKGROUND AND PURPOSE
Hirudin variants are the most powerful thrombin inhibitors discovered to date, with a lower risk of bleeding than heparin. For anticoagulation, the C-termini of hirudin variants bind to the exocite I of thrombin. Anticoagulant effects of gene-recombinant hirudin are weaker than natural hirudin for the reason of lacking tyrosine O-sulfation at C-terminus.
EXPERIMENTAL APPROACH
An integrative pharmacological study was carried out using molecular dynamic, molecular biological and in vivo and in vitro experiments to elucidate the anticoagulant effects of protein-engineered hirudins.
KEY RESULTS
Molecular dynamic analysis showed that modifications of the C-termini of hirudin variant 1 of Hirudo medicinalis (HV1) and hirudin variant 2 of Hirudinaria manillensis (HM2) changed the binding energy of the C-termini to human thrombin. The study indicated that Asp61 of HM2 that corresponds to sulfated Tyr63 of HV1 is critical for inhibiting thrombin activities. Further, the anticoagulant effects of HV1 and HM2 were improved when the amino acid residues adjacent to Asp61 were mutated to Asp. These improvements were prolongation of the activated partial thromboplastin time, prothrombin time and thrombin time of human blood, and decreased K and IC values. In the in vivo experiments, mutations at C-termini of HV1 and HM2 significantly changed partial thromboplastin time, prothrombin and thrombin time CONCLUSION AND IMPLICATIONS: The study indicated that the anticoagulant effects of gene-engineered HM2 are stronger than gene-engineered HV1 and HM2-E60D-I62D has the strongest effects and could be an antithrombotic with better therapeutic effects.
Topics: Amino Acid Sequence; Animals; Anticoagulants; Hirudins; Hirudo medicinalis; Humans; Molecular Dynamics Simulation; Recombinant Proteins; Thrombin
PubMed: 35135035
DOI: 10.1111/bph.15816 -
Molecules (Basel, Switzerland) Dec 2022Cannabinoid receptor ligands are renowned as being therapeutically crucial for treating diverse health disorders. Phenylspirodrimanes are meroterpenoids with unique and...
Cannabinoid receptor ligands are renowned as being therapeutically crucial for treating diverse health disorders. Phenylspirodrimanes are meroterpenoids with unique and varied structural scaffolds, which are mainly reported from the genus and display an array of bioactivities. In this work, 114 phenylspirodrimanes reported from were screened for their CB2 agonistic potential using docking and molecular dynamic simulation studies. Compound revealed the highest docking score (-11.222 kcal/mol) compared to _6KPF (native agonist, gscore value -12.12 kcal/mol). The molecular docking and molecular simulation results suggest that compound binds to the putative binding site in the CB2 receptor with good affinity involving key interacting amino acid residues similar to that of the native ligands, . The molecular interactions displayed π-π stacking with Phe183 and hydrogen bond interactions with Thr114, Leu182, and Ser285. These findings identified the structural features of these metabolites that might lead to the design of selective novel ligands for CB2 receptors. Additionally, phenylspirodrimanes should be further investigated for their potential as a CB2 ligand.
Topics: Binding Sites; Cannabinoid Receptor Agonists; Ligands; Molecular Docking Simulation; Molecular Dynamics Simulation; Receptor, Cannabinoid, CB2; Terpenes
PubMed: 36615238
DOI: 10.3390/molecules28010044 -
Biophysical Journal May 2020The nuclear environment is highly crowded by biological macromolecules, including chromatin and mobile proteins, which alter the kinetics and efficiency of...
The nuclear environment is highly crowded by biological macromolecules, including chromatin and mobile proteins, which alter the kinetics and efficiency of transcriptional machinery. These alterations have been described, both theoretically and experimentally, for steady-state crowding densities; however, temporal changes in crowding density ("dynamic crowding") have yet to be integrated with gene expression. Dynamic crowding is pertinent to nuclear biology because processes such as chromatin translocation and protein diffusion lend to highly mobile biological crowders. Therefore, to capture such dynamic crowding and investigate its influence on transcription, we employ a three-pronged, systems-molecular approach. A system of chemical reactions represents the transcription pathway, the rates of which are determined by molecular-scale simulations; Brownian dynamics and Monte Carlo simulations quantify protein diffusion and DNA-protein binding affinity, dependent on macromolecular density. Altogether, this approach shows that transcription depends critically on dynamic crowding as the gene expression resultant from dynamic crowding can be profoundly different than that of steady-state crowding. In fact, expression levels can display both amplification and suppression and are notably different for genes or gene populations with different chemical and structural properties. These properties can be exploited to impose circadian expression, which is asymmetric and varies in strength, or to explain expression in cells under biomechanical stress. Therefore, this work demonstrates that dynamic crowding nontrivially alters transcription kinetics and presents dynamic crowding within the bulk nuclear nanoenvironment as a novel regulatory framework for gene expression.
Topics: Diffusion; Kinetics; Macromolecular Substances; Molecular Dynamics Simulation; Protein Binding
PubMed: 31818468
DOI: 10.1016/j.bpj.2019.11.007 -
Molecules (Basel, Switzerland) Dec 2021Bromodomain and extra-terminal domain (BET) subfamily is the most studied subfamily of bromodomain-containing proteins (BCPs) family which can modulate acetylation...
Bromodomain and extra-terminal domain (BET) subfamily is the most studied subfamily of bromodomain-containing proteins (BCPs) family which can modulate acetylation signal transduction and produce diverse physiological functions. Thus, the BET family can be treated as an alternative strategy for targeting androgen-receptor (AR)-driven cancers. In order to explore the effect of inhibitors binding to BRD4 (the most studied member of BET family), four 150 ns molecular dynamic simulations were performed (free BRD4, Cpd4-BRD4, Cpd9-BRD4 and Cpd19-BRD4). Docking studies showed that Cpd9 and Cpd19 were located at the active pocket, as well as Cpd4. Molecular dynamics (MD) simulations indicated that only Cpd19 binding to BRD4 can induce residue Trp81-Ala89 partly become α-helix during MD simulations. MM-GBSA calculations suggested that Cpd19 had the best binding effect with BRD4 followed by Cpd4 and Cpd9. Computational alanine scanning results indicated that mutations in Phe83 made the greatest effects in Cpd9-BRD4 and Cpd19-BRD4 complexes, showing that Phe83 may play crucial roles in Cpd9 and Cpd19 binding to BRD4. Our results can provide some useful clues for further BCPs family search.
Topics: Acetylation; Alanine; Amino Acid Sequence; Binding Sites; Cell Cycle Proteins; Humans; Ligands; Molecular Dynamics Simulation; Principal Component Analysis; Protein Binding; Protein Conformation; Protein Domains; Transcription Factors
PubMed: 35011350
DOI: 10.3390/molecules27010118 -
Molecules (Basel, Switzerland) Oct 2022This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of... (Review)
Review
This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of atomic-resolution explicit-solvent molecular dynamics simulations on these and other hyaluronan and hyaluronan-containing systems. Advances in accurate molecular mechanics force fields, simulation methods and software, and computer hardware have supported a recent flourish in such simulations, such that the simulation publications now outnumber the structural biology publications by an order of magnitude. In addition to supplementing the experimental structural biology with computed dynamic and thermodynamic information, the molecular dynamics studies provide a wealth of atomic-resolution information on hyaluronan-containing systems for which there is no atomic-resolution structural biology either available or possible. Examples of these summarized in this review include hyaluronan pairing with other hyaluronan molecules and glycosaminoglycans, with ions, with proteins and peptides, with lipids, and with drugs and drug-like molecules. Despite limitations imposed by present-day computing resources on system size and simulation timescale, atomic-resolution explicit-solvent molecular dynamics simulations have been able to contribute significant insight into hyaluronan's flexibility and capacity for intra- and intermolecular non-covalent interactions.
Topics: Molecular Dynamics Simulation; Hyaluronic Acid; Proteins; Molecular Biology; Solvents
PubMed: 36364098
DOI: 10.3390/molecules27217276 -
Biomolecules May 2020Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and have attracted significant interest in understanding if and how they may be... (Review)
Review
Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and have attracted significant interest in understanding if and how they may be targeted using small molecules for therapeutic purposes. While most existing studies have focused on extending the traditional structure-centric drug design strategies and emphasized exploring pre-existing structure features of IDPs for specific binding, several examples have also emerged to suggest that small molecules could achieve specificity in binding IDPs and affect their function through dynamic and transient interactions. These dynamic interactions can modulate the disordered conformational ensemble and often lead to modest compaction to shield functionally important interaction sites. Much work remains to be done on further elucidation of the molecular basis of the dynamic small molecule-IDP interaction and determining how it can be exploited for targeting IDPs in practice. These efforts will rely critically on an integrated experimental and computational framework for disordered protein ensemble characterization. In particular, exciting advances have been made in recent years in enhanced sampling techniques, Graphic Processing Unit (GPU)-computing, and protein force field optimization, which have now allowed rigorous physics-based atomistic simulations to generate reliable structure ensembles for nontrivial IDPs of modest sizes. Such de novo atomistic simulations will play crucial roles in exploring the exciting opportunity of targeting IDPs through dynamic interactions.
Topics: Humans; Intrinsically Disordered Proteins; Magnetic Resonance Spectroscopy; Molecular Dynamics Simulation; Protein Aggregates; Protein Binding; Protein Structure, Secondary
PubMed: 32403216
DOI: 10.3390/biom10050743 -
Molecules (Basel, Switzerland) Feb 2023A growing body of evidence suggests that only a few amino acids ("hot-spots") at the interface contribute most of the binding energy in transient protein-protein...
A growing body of evidence suggests that only a few amino acids ("hot-spots") at the interface contribute most of the binding energy in transient protein-protein interactions. However, experimental protocols to identify these hot-spots are highly labor-intensive and expensive. Computational methods, including evolutionary couplings, have been proposed to predict the hot-spots, but they generally fail to provide details of the interacting amino acids. Here we showed that unbiased evolutionary methods followed by biased molecular dynamic simulations could achieve this goal and reveal critical elements of protein complexes. We applied the methodology to selected G-protein coupled receptors (GPCRs), known for their therapeutic properties. We used the structure-prior-assisted direct coupling analysis (SP-DCA) to predict the binding interfaces of A2aR/D2R, CB1R/D2R, A2aR/CB1R, 5HT2AR/D2R, and 5-HT2AR/mGluR2 receptor heterodimers, which all agreed with published data. In order to highlight details of the interactions, we performed molecular dynamic (MD) simulations using the newly developed AWSEM energy model. We found that these receptors interact primarily through critical residues at the C and N terminal domains and the third intracellular loop (ICL3). The MD simulations showed that these residues are energetically necessary for dimerization and revealed their native conformational state. We subsequently applied the methodology to the 5-HT2AR/5-HTR4R heterodimer, given its implication in drug addiction and neurodegenerative pathologies such as Alzheimer's disease (AD). Further, the SP-DCA analysis showed that 5-HT2AR and 5-HTR4R heterodimerize through the C-terminal domain of 5-HT2AR and ICL3 of 5-HT4R. However, elucidating the details of GPCR interactions would accelerate the discovery of druggable sites and improve our knowledge of the etiology of common diseases, including AD.
Topics: Molecular Dynamics Simulation; Receptors, G-Protein-Coupled; Cell Membrane; Dimerization; Amino Acids
PubMed: 36838825
DOI: 10.3390/molecules28041838