SWI1 is a member of a new class of tumor DNA-binding proteins named as the AT-rich interaction domain family (ARID), and considered to bind with AT base pairs specifically. Genomic and functional data support ARID1A as a tumor suppressor because ARID1A/BAF250a (SWI1) subunit of the SWI/SNF chromatin-remodeling complex has emerged as recurrently mutated in a broad array of tumor types. But the crystal structure of SWI1 has not been solved as yet. Using docking and molecular dynamics, we predicted the DNA interaction pattern of human SWI1 ARID and made comparisons with the other two representative ARID family members, human Mrf-2 ARID and Drosophila Dri ARID. Dynamic results revealed that the N-terminal and loop L1 of SWI1 ARID bound with the DNA major groove, while the loop L2 and helix H6 bound with the minor groove. Moreover, it was found that SWI1 ARID bound with DNA apparently in a sequence-nonspecific manner. It was concluded that SWI1 ARID can form stable complex with sequence-nonspecific DNA segment comparing to Mrf-2 ARID/DNA and Dri ARID/DNA sequence-specific complexes.
Binding Sites ; DNA ; chemistry ; metabolism ; DNA-Binding Proteins ; chemistry ; metabolism ; Drosophila Proteins ; chemistry ; Homeodomain Proteins ; chemistry ; Humans ; Models, Molecular ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Nuclear Proteins ; chemistry ; Protein Structure, Tertiary ; Transcription Factors ; chemistry ; metabolism

Objectives: This study aims to assess the drug-likeness and binding of nucleobase-substituted ponatinib analogues towards wild-type and T315I mutant BCR-ABL tyrosine kinases. Methodology: A total of 415 ponatinib analogues, encompassing single and combinatorial modifications on five parts of the drug were generated, profiled in SwissADME, and subjected to molecular docking using AutoDock4. Complexes formed by the top analogues then underwent a 100-ns molecular dynamics simulation with GROMACS. Results: Analogues featuring the replacement of the imidazo[1,2b]pyridazine with adenine and cytosine exhibited promising binding free energies, attributed to the presence of primary amines that facilitate crucial hydrogen bond interactions in the hinge region. RMSD, RMSF, and atomic distance analyses of the MD trajectories revealed that the six top analogues formed stable complexes in their inactive DFG-out conformations. Changes in the MMPBSA and MMGBSA-calculated free energies were mainly driven by changes in hydrogen bonds. Furthermore, drug-likeness predictions supported the formulation of most analogues for oral administration. Conclusion Among the top analogues, VP10004 and VP81014 exhibited the most favorable binding free energies and interactions with the target models, while VP10312 was identified as the most feasible candidate for synthesis.
Hydrogen Bonding ; Molecular Dynamics Simulation ; Molecular Docking Simulation

Fatty acid synthase (FASN, EC 2.3.1.85), is a multi-enzyme dimer complex that plays a critical role in lipogenesis. This lipogenic enzyme has gained importance beyond its physiological role due to its implications in several clinical conditions-cancers, obesity, and diabetes. This has made FASN an attractive pharmacological target. Here, we have attempted to predict the theoretical models for the human enoyl reductase (ER) and beta-ketoacyl reductase (KR) domains based on the porcine FASN crystal structure, which was the structurally closest template available at the time of this study. Comparative modeling methods were used for studying the structure-function relationships. Different validation studies revealed the predicted structures to be highly plausible. The respective substrates of ER and KR domains-namely, trans-butenoyl and beta-ketobutyryl-were computationally docked into active sites using Glide in order to understand the probable binding mode. The molecular dynamics simulations of the apo and holo states of ER and KR showed stable backbone root mean square deviation trajectories with minimal deviation. Ramachandran plot analysis showed 96.0% of residues in the most favorable region for ER and 90.3% for the KR domain, respectively. Thus, the predicted models yielded significant insights into the substrate binding modes of the ER and KR catalytic domains and will aid in identifying novel chemical inhibitors of human FASN that target these domains.
Catalytic Domain* ; Humans ; Lipogenesis ; Models, Theoretical ; Molecular Dynamics Simulation* ; Obesity ; Oxidoreductases*

In this study, bioinformatics methods such as molecular docking and network pharmacology were adopted to establish Xiaoxuming Decoction (XXMD) "compound-vasodilatory and vasoconstrictory related G protein-coupled receptors (GPCR) targets" network, then the vascular function regulatory effective components and the potential targets of XXMD were analyzed. Based on the XXMD herb sources, the chemical structures of the compounds were retrieved from the national scientific data sharing platform for population and health pharmaceutical information center, TCMSP database and the latest research literatures. The chemical molecular library was established after class prediction and screening for medicinal and metabolic properties. Then, five kinds of vasodilatory and vasoconstrictory related GPCR crystal structure including 5-HT receptors (5-HT1AR, 5-HT1BR), AT1R, β2-AR, hUTR and ETB were retrieved from RCSB Protein Data Bank database or constructed by homology modeling of Discovery Studio 4.1 built-in modeling tools. After virtual screening by Libdock molecular docking, the highest rated 50 compounds of each target were collected and analyzed. The collected data were further used to construct and analyze the network by Cytoscape 3.4.0. The results showed that most of the chemical composition effects were associated with different vasodilatory and vasoconstrictory related GPCR targets, while a few effective components could be applied to multiple GPCR targets at the same time, therefore forming synergies and vasorelaxant effects of XXMD.
Databases, Protein ; Drugs, Chinese Herbal ; Models, Chemical ; Molecular Docking Simulation ; Receptors, G-Protein-Coupled ; metabolism ; Vasodilation

Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.
Computational Biology ; Drug Design ; Drug Discovery ; High-Throughput Screening Assays ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Quantitative Structure-Activity Relationship

Toxoplasma gondii is an intracellular Apicomplexan parasite and a causative agent of toxoplasmosis in human. It causes encephalitis, uveitis, chorioretinitis, and congenital infection. T. gondii invades the host cell by forming a moving junction (MJ) complex. This complex formation is initiated by intermolecular interactions between the two secretory parasitic proteins—namely, apical membrane antigen 1 (AMA1) and rhoptry neck protein 2 (RON2) and is critically essential for the host invasion process. By this study, we propose two potential leads, NSC95522 and NSC179676 that can efficiently target the AMA1 hydrophobic cleft, which is a hotspot for targeting MJ complex formation. The proposed leads are the result of an exhaustive conformational search-based virtual screen with multilevel precision scoring of the docking affinities. These two compounds surpassed all the precision levels of docking and also the stringent post docking and cumulative molecular dynamics evaluations. Moreover, the backbone flexibility of hotspot residues in the hydrophobic cleft, which has been previously reported to be essential for accommodative binding of RON2 to AMA1, was also highly perturbed by these compounds. Furthermore, binding free energy calculations of these two compounds also revealed a significant affinity to AMA1. Machine learning approaches also predicted these two compounds to possess more relevant activities. Hence, these two leads, NSC95522 and NSC179676, may prove to be potential inhibitors targeting AMA1-RON2 complex formation towards combating toxoplasmosis.
Chorioretinitis ; Drug Design ; Encephalitis ; Humans ; Hydrophobic and Hydrophilic Interactions ; Machine Learning ; Membranes* ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Neck ; Parasites ; Pliability ; Toxoplasma* ; Toxoplasmosis ; Uveitis

CB2-selective agonists have drawn attention in drug discovery, since CB2 becomes a promising target for the treatment of neuropathic pain without psychoactive or other CNS-related side effects. However, the lack of experimental data of the 3D structures of human cannabinoid receptors hampers the understanding of the binding modes between ligands and CB2 by traditional methods. In the present work, combinational molecular modeling studies including flexible docking, MD simulations and free energy calculations were performed to investigate the interaction modes and mechanism of CB2-unselective agonist CP55940 and CB2-selective agonist GW842166X, separately binding with the homology model of CB2 in a DPPC/TIP3P simulated membrane environment. The binding free energies calculated by MM-PBSA method give an explanation for the activity differences of the studied ligands. Binding free energies decomposition by MM-GBSA method shows that the van der Waals interaction is the dominant driving force during the binding process. Our MD simulations demonstrate that Phe197 could be a critical residue for the binding of CB2-selective agonists. Furthermore, by using the MD simulated binding conformer as a template, the 3D-QSAR studies were performed with the comparative molecular field analysis (CoMFA) approach on a set of GW842166X analogues. A combinational exploration of both CoMFA steric and potential contour maps for CB2 affinities and the MD studied interaction modes sheds light on the structural requirements for CB2 agonists and serves as a basis for the design of novel CB2 agonists.
Binding Sites ; Cyclohexanols ; chemistry ; Humans ; Ligands ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Protein Binding ; Pyrans ; chemistry ; Pyrimidines ; chemistry ; Quantitative Structure-Activity Relationship ; Receptor, Cannabinoid, CB2 ; agonists ; chemistry

We review major computational chemistry techniques applied in industrial enzyme studies, especially approaches intended for guiding enzyme engineering. These include molecular mechanics force field and molecular dynamics simulation, quantum mechanical and combined quantum mechanical/molecular mechanical approaches, electrostatic continuum models, molecular docking, etc. These approaches are essentially introduced from the following two angles for viewing: one is about the methods themselves, including the basic concepts, the primary computational results, and potential advantages and limitations; the other is about obtaining valuable information from the respective calculations to guide the design of mutants and mutant libraries.
Enzymes ; chemistry ; genetics ; metabolism ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Mutant Proteins ; chemistry ; genetics ; metabolism ; Protein Engineering ; Quantum Theory ; Static Electricity

We aim to screen out the active components that may have therapeutic effect on coronavirus disease 2019 (COVID-19) from the severe and critical cases' prescriptions in the "Coronavirus Disease 2019 Diagnosis and Treatment Plan (Trial Ninth Edition)" issued by the National Health Commission of the People's Republic of China and explain its mechanism through the interactions with proteins. The ETCM database and SwissADME database were used to screen the active components contained in 25 traditional Chinese medicines in 3 prescriptions, and the PDB database was used to obtain the crystal structures of 4 proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Molecular docking was performed using Autodock Vina and molecular dynamics simulations were performed using GROMACS. Binding energy results showed that 44 active ingredients including xambioona, gancaonin L, cynaroside, and baicalin showed good binding affinity with multiple targets of SARS-CoV-2, while molecular dynamics simulations analysis showed that xambioona bound more tightly to the nucleocapsid protein of SARS-CoV-2 and exerted a potent inhibitory effect. Modern technical methods are used to study the active components of traditional Chinese medicine and show that xambioona is an effective inhibitor of SARS-CoV-2 nucleocapsid protein, which provides a theoretical basis for the development of new anti-SARS-CoV-2 drugs and their treatment methods.
Humans ; SARS-CoV-2 ; Molecular Docking Simulation ; Medicine, Chinese Traditional ; Molecular Dynamics Simulation ; Nucleocapsid Proteins ; Antiviral Agents/pharmacology* ; COVID-19 Drug Treatment

Antiviral Agents/pharmacology* ; COVID-19 ; Coronavirus 3C Proteases ; Humans ; Lactams ; Leucine ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Nitriles ; Proline ; Protease Inhibitors/pharmacology* ; SARS-CoV-2