scholarly journals Molecular dynamics simulations and in vitro analysis of the CRMP2 thiol switch

2017 ◽  
Vol 13 (9) ◽  
pp. 1744-1753 ◽  
Author(s):  
Daniel Möller ◽  
Manuela Gellert ◽  
Walter Langel ◽  
Christopher Horst Lillig
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Neuronal Development ◽  
Collapsin Response Mediator Protein ◽  
Mediator Protein ◽  
Thiol Switch ◽  
Dynamics Simulations ◽  
Vitro Analysis ◽  
In Vitro Analysis

The collapsin response mediator protein CRMP2 (gene: DPYSL2) is crucial for neuronal development.

Molecular Basis of Iterative C–H Oxidation by TamI, a Multifunctional P450 Monooxygenase from the Tirandamycin Biosynthetic Pathway

2020 ◽  
Author(s):  
Sean A. Newmister ◽  
Kinshuk Raj Srivastava ◽  
Rosa V. Espinoza ◽  
Kersti Caddell Haatveit ◽  
Yogan Khatri ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Molecular Basis ◽  
Hydrophobic Interactions ◽  
Cytochromes P450 ◽  
Targeted Mutagenesis ◽  
P450 Monooxygenase ◽  
Bond Functionalization ◽  
Dynamics Simulations

Biocatalysis offers an expanding and powerful strategy to construct and diversify complex molecules by C-H bond functionalization. Due to their high selectivity, enzymes have become an essential tool for C-H bond functionalization and offer complementary reactivity to small-molecule catalysts. Hemoproteins, particularly cytochromes P450, have proven effective for selective oxidation of unactivated C-H bonds. Previously, we reported the in vitro characterization of an oxidative tailoring cascade in which TamI, a multifunctional P450 functions co-dependently with the TamL flavoprotein to catalyze regio- and stereoselective hydroxylations and epoxidation to yield tirandamycin A and tirandamycin B. TamI follows a defined order including 1) C10 hydroxylation, 2) C11/C12 epoxidation, and 3) C18 hydroxylation. Here we present a structural, biochemical, and computational investigation of TamI to understand the molecular basis of its substrate binding, diverse reactivity, and specific reaction sequence. The crystal structure of TamI in complex with tirandamycin C together with molecular dynamics simulations and targeted mutagenesis suggest that hydrophobic interactions with the polyene chain of its natural substrate are critical for molecular recognition. QM/MM calculations and molecular dynamics simulations of TamI with variant substrates provided detailed information on the molecular basis of sequential reactivity, and pattern of regio- and stereo-selectivity in catalyzing the three-step oxidative cascade.<br>

Υπολογιστικά εργαλεία για την αναζήτηση νέων βιοδραστικών ενώσεων σε επιλεγμένους πρωτεϊνικούς στόχους

2017 ◽  
Author(s):  
Ευτυχία Κρίτση
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Molecular Dynamics Simulations ◽  
In Silico ◽  
Pharmacophore Modeling ◽  
Lead Optimization ◽  
Dynamics Simulations ◽  
Hiv 1

Στην παρούσα διατριβή πραγματοποιήθηκε εκτενής μελέτη για την αναζήτηση πρόδρομων βιοδραστικών ενώσεων (hits) από χημικές βιβλιοθήκες για τρείς βιολογικούς στόχους, μέσω της εφαρμογής εμπορικά διαθέσιμων in silico τεχνικών και μεθοδολογιών.Οι στόχοι που επιλέχθηκαν ανήκουν σε διαφορετικές κατηγορίες πρωτεϊνών με μεγάλο φαρμακευτικό ενδιαφέρον, που όμως παρουσιάζουν διαφορετικό επίπεδο ωριμότητας όσον αφορά την εφαρμογή υπολογιστικών εργαλείωνγια την ανακάλυψη νέων φαρμακευτικών ενώσεων. Συγκεριμένα, οι στόχοι που μελετήθηκαν είναι οι ακόλουθοι:•το ένζυμο της 14-α διμεθυλάσης της λανοστερόλης (CYP51) για την αναζήτηση νέων πρόδρομων βιοδραστικών ενώσεων με αντιμικροβιακές ιδιότητες,•το ένζυμο της HIV τύπου 1 πρωτεάσης (HIV-1 PR) για την αναζήτηση νέων πρόδρομων βιοδραστικών ενώσεων με αντι-HIV δράση,•ο διαμεμβρανικός υποδοχέας της Αγγειοτασίνης ΙΙ (ΑΤ1) για την αναζήτηση νέων πρόδρομων βιοδραστικών με αντιυπερτασική δράσηΟι κυριότερες τεχνικές που χρησιμοποιήθηκαν για την αναζήτηση πρόδρομων βιοδραστικών ενώσεων περιλαμβάνουν την Εικονική Σάρωση (Virtual Screening) με χρήση Φαρμακοφόρων Μοντέλων (Pharmacophore modeling), τη Μοριακή Πρόσδεση (Molecular Docking), την πρόβλεψη μοριακών ιδιοτήτων καθώς και Προσομοιώσεις Μοριακής Δυναμικής (Molecular Dynamics Simulations). Η στρατηγική που ακολουθήθηκε διαφέρει σημαντικά ανά στόχο όσον αφορά τη μεθοδολογική προσέγγιση και την επιλογή των υπολογιστικών εργαλείων-αλγορίθμων, δίνοντας έμφαση στη συμπληρωματικότητα των αποτελεσμάτων τους. Για την ανάδειξη των πρόδρομων βιοδραστικών ενώσεων, πραγματοποιήθηκαν in vitro βιολογικές δοκιμές των ενώσεων που προτάθηκαν μέσω των υπολογιστικών τεχνικών. Οι ενώσεις που επιλέχθηκαν παρουσίασαν ανασταλτική δράση (ή συγγένεια πρόσδεσης) σε ικανοποιητικό εύρος τιμών 102 nM–μΜ για να χαρακτηριστούν πρόδρομες βιοδραστικές. Μείζονος σημασίας είναι και το γεγονός ότι οι δομικοί σκελετοί των προτεινόμενων ενώσεων για κάθε στόχο, είναι διαφορετικοί τόσο μεταξύ τους όσο και συγκρινόμενοι με τα υφιστάμενα φαρμακευτικά μόρια. Ως εκ τούτου, μπορούν να αποτελέσουν κατάλληλα "υποστρώματα" για το επόμενο στάδιο που αφορά τη βελτιστοποίησή τους προς ενώσεις-οδηγούς (hit to lead optimization) και δυνητικά προς νέα φαρμακευτικά προϊόντα.

scholarly journals Coumarin derivatives as acetyl- and butyrylcholinestrase inhibitors: An in vitro, molecular docking, and molecular dynamics simulations study

Heliyon ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. e01552 ◽  
Author(s):  
Marwa N. Abu-Aisheh ◽  
Amal Al-Aboudi ◽  
Mohammad S. Mustafa ◽  
Mustafa M. El-Abadelah ◽  
Saman Yousuf Ali ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Coumarin Derivatives ◽  
Dynamics Simulations

scholarly journals Exploring Aurone Derivatives as Potential Human Pancreatic Lipase Inhibitors through Molecular Docking and Molecular Dynamics Simulations

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4657
Author(s):  
Phuong Thuy Viet Nguyen ◽  
Han Ai Huynh ◽  
Dat Van Truong ◽  
Thanh-Dao Tran ◽  
Cam-Van Thi Vo
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Pancreatic Lipase ◽  
Inhibitory Activity ◽  
Dynamics Simulation ◽  
Stable Complex ◽  
Catalytic Active Site ◽  
Dynamics Simulations

Inhibition of human pancreatic lipase, a crucial enzyme in dietary fat digestion and absorption, is a potent therapeutic approach for obesity treatment. In this study, human pancreatic lipase inhibitory activity of aurone derivatives was explored by molecular modeling approaches. The target protein was human pancreatic lipase (PDB ID: 1LPB). The 3D structures of 82 published bioactive aurone derivatives were docked successfully into the protein catalytic active site, using AutoDock Vina 1.5.7.rc1. Of them, 62 compounds interacted with the key residues of catalytic trial Ser152-Asp176-His263. The top hit compound (A14), with a docking score of −10.6 kcal⋅mol−1, was subsequently submitted to molecular dynamics simulations, using GROMACS 2018.01. Molecular dynamics simulation results showed that A14 formed a stable complex with 1LPB protein via hydrogen bonds with important residues in regulating enzyme activity (Ser152 and Phe77). Compound A14 showed high potency for further studies, such as the synthesis, in vitro and in vivo tests for pancreatic lipase inhibitory activity.

Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs

2014 ◽  
Vol 169 ◽  
pp. 303-321 ◽  
Author(s):  
Ariane Allain ◽  
Isaure Chauvot de Beauchêne ◽  
Florent Langenfeld ◽  
Yann Guarracino ◽  
Elodie Laine ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Network Analysis ◽  
Molecular Dynamics Simulations ◽  
Large Scale ◽  
Allosteric Regulation ◽  
Local Perturbation ◽  
Modular Network ◽  
Allosteric Coupling ◽  
Dynamics Simulations

Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach – MOdular NETwork Analysis (MONETA) – based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins – a crucial basis to guide the discovery of next-generation allosteric drugs.

scholarly journals Interrogating RNA-small molecule interactions with structure probing and AI augmented-molecular simulations

2021 ◽  
Author(s):  
Yihang Wang ◽  
Shaifaly Parmar ◽  
John S. Schneekloth ◽  
Pratyush Tiwary
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Ligand Recognition ◽  
Binding Affinities ◽  
Structure Probing ◽  
Mutational Profiling ◽  
In Vitro Measurements ◽  
Molecule Interactions ◽  
Dynamics Simulations

While there is increasing interest in the study of RNA as a therapeutic target, efforts to understand RNA-ligand recognition at the molecular level lag far behind our understanding of protein-ligand recognition. This problem is complicated due to the more than ten orders of magnitude in timescales involved in RNA dynamics and ligand binding events, making it not straightforward to design experiments or simulations. Here we make use of artificial intelligence (AI)-augmented molecular dynamics simulations to directly observe ligand dissociation for cognate and synthetic ligands from a riboswitch system. The site-specific flexibility profiles from our simulations are in excellent agreement with in vitro measurements of flexibility using Selective 2' Hydroxyl Acylation analyzed by Primer Extension and Mutational Profiling (SHAPE-MaP). Our simulations reproduce known binding affinity profiles for the cognate and synthetic ligands, and pinpoint how both ligands make use of different aspects of riboswitch flexibility. On the basis of our dissociation trajectories, we also make and validate predictions of pairs of mutations for both the ligand systems that would show differing binding affinities. These mutations are distal to the binding site and could not have been predicted solely on the basis of structure. The methodology demonstrated here shows how molecular dynamics simulations with all-atom force-fields have now come of age in making predictions that complement existing experimental techniques and illuminate aspects of systems otherwise not trivial to understand.

Sign in / Sign up

Export Citation Format

Share Document