scholarly journals In-silico predictive identification of K-RasG12V inhibitors in natural compounds

2019 ◽  
Author(s):  
Masoud Aliyar ◽  
Hassan Aryapour ◽  
Majid Mahdavi
Keyword(s):  
Small Molecules ◽  
Drug Target ◽  
Binding Free Energy ◽  
Structure Based Drug Design ◽  
Ras Protein ◽  
Colon Cancers ◽  
Reference Ligand ◽  
Calculation Results ◽  
Poisson Boltzmann ◽  
Dynamics Simulations

AbstractAs RAS protein is highly significant in signaling pathways, involving cell growth, differentiation and apoptosis; the Ras GTPase proteins play a significant as a master switch in the appearance of many diseases, including 20-30% of all cancers. So, the K-RasG12V mutant was selected as a drug target in present study. This mutant is involved in gastric cancer, lung and pancreatic carcinoma, and colon cancers. So, we employed the structure-based drug design methods and molecular dynamics simulations to undergo virtual screening on natural products small molecules and predicted some new potent therapeutic inhibitors. Finally, ZINC15671852, ZINC85592862, ZINC85567582 and ZINC03616630 final Hits were identified as potent inhibitors from among more than 79,000 bioactive compounds from natural resource. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-P/GBSA) calculation results have also demonstrated that these molecules obtained higher binding free energy than co-crystalized reference ligand.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

2019 ◽  
Vol 25 (31) ◽  
pp. 3339-3349 ◽  
Author(s):  
Indrani Bera ◽  
Pavan V. Payghan
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Drug Target ◽  
Structural Information ◽  
Drug Binding ◽  
Structure Based Drug Design ◽  
Drug Designing ◽  
Target Binding ◽  
Dynamics Simulations

Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. Objective: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. Method: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. Results: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. Conclusion: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

scholarly journals All-Atom MD Simulations of the HBV Capsid Complexed with AT130 Reveal Secondary and Tertiary Structural Changes and Mechanisms of Allostery

2021 ◽  
Author(s):  
Carolina Pérez Segura ◽  
Boon Chong Goh ◽  
Jodi A. Hadden-Perilla
Keyword(s):  
Small Molecules ◽  
Drug Target ◽  
Structural Changes ◽  
Salt Bridge ◽  
Md Simulations ◽  
Health Concern ◽  
Protein Dimer ◽  
B Virus ◽  
Flexible Protein ◽  
Dynamics Simulations

AbstractThe hepatitis B virus (HBV) capsid is an attractive drug target, relevant to combating viral hepatitis as a major public health concern. Among small molecules known to interfere with capsid assembly, the phenylpropenamides, including AT130, represent an important anti-viral paradigm based on disrupting the timing of genome encapsulation. Crystallographic studies of AT130-bound complexes have been essential in explaining the effects of the small molecule on HBV capsid structure; however, computational examination reveals that key changes attributed to AT130 were erroneous, likely a consequence of interpreting poor resolution arising from a highly flexible protein. Here, all-atom molecular dynamics simulations of an intact AT130-bound HBV capsid reveal that, rather than damaging spike helicity, AT130 enhances the capsid’s ability to recover it. A new conformational state is identified, which can lead to dramatic opening of the intradimer interface and disruption of communication within the spike tip. A novel salt bridge is also discovered, which can mediate contact between the spike tip and fulcrum even in closed conformations, revealing a mechanism of direct communication across these domains. Combined with dynamical network analysis, results describe a connection between the intra- and interdimer interfaces and enable mapping of allostery traversing the entire capsid protein dimer.

scholarly journals Fragment tailoring strategy to design novel chemical entities as potential binders of novel corona virus main protease

2020 ◽  
Author(s):  
chinmayee choudhury
Keyword(s):  
Binding Site ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Corona Virus ◽  
Main Protease ◽  
New Chemical Entities ◽  
Reference Ligand ◽  
Binding Cavity ◽  
Binding Pockets ◽  
Dynamics Simulations

<p></p><p>The recent pandemic of novel corona virus (nCoV) infections (COVID19) has put the world on serious alert. The main protease of nCov (nCov-MP) cleaves the long polyprotein chains to release functional proteins required for replication of the virus and thus is a potential drug target to design new chemical entities in order to inhibit the viral replication in human cells. The current study employs state of art computational methods to design novel molecules by linking molecular fragments which specifically bind to different constituent sub-pockets of the nCov-MP binding site. A huge library of 191678 fragments was screened against the binding cavity of nCov-MP and high affinity fragments binding to adjacent sub-pockets were tailored to generate new molecules. These newly formed molecules were further subjected to molecular docking, ADMET property filters and MM-GBSA binding free energy calculations to select 17 best molecules (named as MP-In1 to Mp-In17), which showed comparable binding affinities and interactions with the key binding site residues as the reference ligand. The complexes of these 17 molecules and the reference molecule with nCov-MP, were subjected to molecular dynamics simulations, which assessed the stabilities of their binding with nCov-MP. Fifteen molecules were found to form stable complexes with nCov-MP. These novel chemical entities designed specifically according to the pharmacophoric requirements of nCov-MP binding pockets showed good synthetic feasibility and returned no exact match when searched against chemical databases. Considering their interactions, binding efficiencies and novel chemotypes, they can be further evaluated as potential starting points for nCov drug discovery. </p><br><p></p>

scholarly journals Identification of Flavonoids as Putative ROS-1 Kinase Inhibitors Using Pharmacophore Modeling for NSCLC Therapeutics

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2114
Author(s):  
Shraddha Parate ◽  
Vikas Kumar ◽  
Jong Chan Hong ◽  
Keun Woo Lee
Keyword(s):  
Kinase Inhibitors ◽  
Binding Free Energy ◽  
Pharmacophore Model ◽  
Kinase Domain ◽  
Pharmacophore Modeling ◽  
Free Energy Calculations ◽  
Wild Type ◽  
Small Cell Lung ◽  
Poisson Boltzmann ◽  
Dynamics Simulations

Non-small cell lung cancer (NSCLC) is a lethal non-immunogenic malignancy and proto-oncogene ROS-1 tyrosine kinase is one of its clinically relevant oncogenic markers. The ROS-1 inhibitor, crizotinib, demonstrated resistance due to the Gly2032Arg mutation. To curtail this resistance, researchers developed lorlatinib against the mutated kinase. In the present study, a receptor-ligand pharmacophore model exploiting the key features of lorlatinib binding with ROS-1 was exploited to identify inhibitors against the wild-type (WT) and the mutant (MT) kinase domain. The developed model was utilized to virtually screen the TimTec flavonoids database and the retrieved drug-like hits were subjected for docking with the WT and MT ROS-1 kinase. A total of 10 flavonoids displayed higher docking scores than lorlatinib. Subsequent molecular dynamics simulations of the acquired flavonoids with WT and MT ROS-1 revealed no steric clashes with the Arg2032 (MT ROS-1). The binding free energy calculations computed via molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) demonstrated one flavonoid (Hit) with better energy than lorlatinib in binding with WT and MT ROS-1. The Hit compound was observed to bind in the ROS-1 selectivity pocket comprised of residues from the β-3 sheet and DFG-motif. The identified Hit from this investigation could act as a potent WT and MT ROS-1 inhibitor.

scholarly journals Fragment tailoring strategy to design novel chemical entities as potential binders of novel corona virus main protease

2020 ◽  
Author(s):  
chinmayee choudhury
Keyword(s):  
Binding Site ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Corona Virus ◽  
Main Protease ◽  
New Chemical Entities ◽  
Reference Ligand ◽  
Binding Cavity ◽  
Binding Pockets ◽  
Dynamics Simulations

<p></p><p>The recent pandemic of novel corona virus (nCoV) infections (COVID19) has put the world on serious alert. The main protease of nCov (nCov-MP) cleaves the long polyprotein chains to release functional proteins required for replication of the virus and thus is a potential drug target to design new chemical entities in order to inhibit the viral replication in human cells. The current study employs state of art computational methods to design novel molecules by linking molecular fragments which specifically bind to different constituent sub-pockets of the nCov-MP binding site. A huge library of 191678 fragments was screened against the binding cavity of nCov-MP and high affinity fragments binding to adjacent sub-pockets were tailored to generate new molecules. These newly formed molecules were further subjected to molecular docking, ADMET property filters and MM-GBSA binding free energy calculations to select 17 best molecules (named as MP-In1 to Mp-In17), which showed comparable binding affinities and interactions with the key binding site residues as the reference ligand. The complexes of these 17 molecules and the reference molecule with nCov-MP, were subjected to molecular dynamics simulations, which assessed the stabilities of their binding with nCov-MP. Fifteen molecules were found to form stable complexes with nCov-MP. These novel chemical entities designed specifically according to the pharmacophoric requirements of nCov-MP binding pockets showed good synthetic feasibility and returned no exact match when searched against chemical databases. Considering their interactions, binding efficiencies and novel chemotypes, they can be further evaluated as potential starting points for nCov drug discovery. </p><br><p></p>

Structure-Based Virtual Screening and Biochemical Evaluation for the Identification of Novel Trypanosoma brucei Aldolase Inhibitors

2018 ◽  
Vol 18 (5) ◽  
pp. 397-405 ◽  
Author(s):  
Leonardo L.G. Ferreira ◽  
Rafaela S. Ferreira ◽  
David L. Palomino ◽  
Adriano D. Andricopulo
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Trypanosoma Brucei ◽  
Enzyme Inhibitor ◽  
Practical Knowledge ◽  
Glycolytic Enzyme ◽  
Structure Based Drug Design ◽  
Biochemical Evaluation ◽  
Dynamics Simulations ◽  
Fructose 1,6 Bisphosphate

Introduction: The glycolytic enzyme fructose-1,6-bisphosphate aldolase is a validated molecular target in human African trypanosomiasis (HAT) drug discovery, a neglected tropical disease (NTD) caused by the protozoan Trypanosoma brucei. Herein, a structure-based virtual screening (SBVS) approach to the identification of novel T. brucei aldolase inhibitors is described. Distinct molecular docking algorithms were used to screen more than 500,000 compounds against the X-ray structure of the enzyme. This SBVS strategy led to the selection of a series of molecules which were evaluated for their activity on recombinant T. brucei aldolase. The effort led to the discovery of structurally new ligands able to inhibit the catalytic activity of the enzyme. Results: The predicted binding conformations were additionally investigated in molecular dynamics simulations, which provided useful insights into the enzyme-inhibitor intermolecular interactions. Conclusion: The molecular modeling results along with the enzyme inhibition data generated practical knowledge to be explored in further structure-based drug design efforts in HAT drug discovery.

scholarly journals Alternative approaches to target Myc for cancer treatment

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Chen Wang ◽  
Jiawei Zhang ◽  
Jie Yin ◽  
Yichao Gan ◽  
Senlin Xu ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Small Molecules ◽  
Drug Target ◽  
The Past ◽  
Physiological Processes ◽  
Alternative Approaches ◽  
Global Transcriptome ◽  
Factor C ◽  
Signaling Modules ◽  
Druggable Targets

AbstractThe Myc proto-oncogene family consists of three members, C-MYC, MYCN, and MYCL, which encodes the transcription factor c-Myc (hereafter Myc), N-Myc, and L-Myc, respectively. Myc protein orchestrates diverse physiological processes, including cell proliferation, differentiation, survival, and apoptosis. Myc modulates about 15% of the global transcriptome, and its deregulation rewires the cellular signaling modules inside tumor cells, thereby acquiring selective advantages. The deregulation of Myc occurs in >70% of human cancers, and is related to poor prognosis; hence, hyperactivated Myc oncoprotein has been proposed as an ideal drug target for decades. Nevertheless, no specific drug is currently available to directly target Myc, mainly because of its “undruggable” properties: lack of enzymatic pocket for conventional small molecules to bind; inaccessibility for antibody due to the predominant nucleus localization of Myc. Although the topic of targeting Myc has actively been reviewed in the past decades, exciting new progresses in this field keep emerging. In this review, after a comprehensive summarization of valuable sources for potential druggable targets of Myc-driven cancer, we also peer into the promising future of utilizing macropinocytosis to deliver peptides like Omomyc or antibody agents to intracellular compartment for cancer treatment.

Computational methods for calculation of protein-ligand binding affinities in structure-based drug design

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Zbigniew Dutkiewicz
Keyword(s):  
Drug Design ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Development Project ◽  
Quantum Mechanical ◽  
Prediction Methods ◽  
Binding Affinities ◽  
Structure Based Drug Design ◽  
Quantum Mechanical Description ◽  
Optimization Stage

AbstractDrug design is an expensive and time-consuming process. Any method that allows reducing the time the costs of the drug development project can have great practical value for the pharmaceutical industry. In structure-based drug design, affinity prediction methods are of great importance. The majority of methods used to predict binding free energy in protein-ligand complexes use molecular mechanics methods. However, many limitations of these methods in describing interactions exist. An attempt to go beyond these limits is the application of quantum-mechanical description for all or only part of the analyzed system. However, the extensive use of quantum mechanical (QM) approaches in drug discovery is still a demanding challenge. This chapter briefly reviews selected methods used to calculate protein-ligand binding affinity applied in virtual screening (VS), rescoring of docked poses, and lead optimization stage, including QM methods based on molecular simulations.

IDENTIFICATION OF SELETIVE CLAUDIN CATION CHANNEL BLOCKERS

2021 ◽  
Vol 27 (Supplement_1) ◽  
pp. S25-S26
Author(s):  
Jingjing Ma ◽  
Emma Wu ◽  
Ye Li ◽  
William Seibel ◽  
Le Shen ◽  
...  
Keyword(s):  
Small Molecules ◽  
Homology Model ◽  
Docking Studies ◽  
Channel Blockers ◽  
Binding Modes ◽  
Barrier Dysfunction ◽  
Epithelial Barrier Function ◽  
Dynamics Simulations ◽  
In Silico Models

Abstract Compromised epithelial barrier function is known to be associated with inflammatory bowel disease (IBD) and may contribute to disease development. One mechanism of barrier dysfunction is increased expression of paracellular tight junction ion and water channels formed by claudins. Claudin-2 and -15 are two such channels. We hypothesize that blocking these channels could be a viable therapeutic approach to treat diarrhea. In an effort to develop blockers of these channels, we turn to our previously developed and validated in silico models of claudin-15 (Samanta et al. 2018). We reasoned that compounds that can bind with the interior of claudin pores can limit paracellular water and ion flux. Thus, we used docking algorithms to search for putative small molecules that bind in the claudin-15 pore. AutoDock Vina was initially used to assess rigid docking using small compound databases. The small molecules were analyzed based on binding affinity to the pore and visualized using VMD for their potential blockage of the channel. Clusters of binding modes were identified based on the prominent interacting residues of the protein with the small molecules. We initially screened 10,500 compounds from within the UIC Centre for Drug Discovery and a cross-section of 10,000 compounds from the NCI open compound repository. This initial screen allowed us to identify 2 first-in-class selective claudin-15 blockers with efficacy in MDCK monolayers induced to express claudin-15 and in wildtype duodenum. Next, we screened the entire NCI open compound repository for additional molecules structurally related to our best initially identified molecule and this has allowed us to identify 13 additional molecules that increase TER of claudin-15 expressing MDCK monolayers by 90–160%. Additionally, these molecules possess similar structural components that will be collected in a fragment library and explored through molecular dynamics simulations. We also developed a claudin-2 homology model on which we are performing docking studies and in vitro measurements, which we expect will result in similar candidate ligands for blocking claudin-2. Our study will provide important insight into the role of claudin-dependent cation permeability in fundamental physiology, which we believe will lead to the utility of claudin blockers as a novel and much needed approach to treat diseases such as IBD.

scholarly journals Online biophysical predictions for SARS-CoV-2 proteins

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Luciano Kagami ◽  
Joel Roca-Martínez ◽  
Jose Gavaldá-García ◽  
Pathmanaban Ramasamy ◽  
K. Anton Feenstra ◽  
...  
Keyword(s):  
Protein Sequence ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Static Structure ◽  
Homologous Proteins ◽  
Structure Based Drug Design ◽  
Protein Protein Interaction ◽  
Link Type ◽  
Dynamics Simulations ◽  
Β Sheet

Abstract Background The SARS-CoV-2 virus, the causative agent of COVID-19, consists of an assembly of proteins that determine its infectious and immunological behavior, as well as its response to therapeutics. Major structural biology efforts on these proteins have already provided essential insights into the mode of action of the virus, as well as avenues for structure-based drug design. However, not all of the SARS-CoV-2 proteins, or regions thereof, have a well-defined three-dimensional structure, and as such might exhibit ambiguous, dynamic behaviour that is not evident from static structure representations, nor from molecular dynamics simulations using these structures. Main We present a website (https://bio2byte.be/sars2/) that provides protein sequence-based predictions of the backbone and side-chain dynamics and conformational propensities of these proteins, as well as derived early folding, disorder, β-sheet aggregation, protein-protein interaction and epitope propensities. These predictions attempt to capture the inherent biophysical propensities encoded in the sequence, rather than context-dependent behaviour such as the final folded state. In addition, we provide the biophysical variation that is observed in homologous proteins, which gives an indication of the limits of their functionally relevant biophysical behaviour. Conclusion The https://bio2byte.be/sars2/ website provides a range of protein sequence-based predictions for 27 SARS-CoV-2 proteins, enabling researchers to form hypotheses about their possible functional modes of action.

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