Large purchasable screening libraries of small molecules afforded by commercial vendors are indispensable sources for virtual screening (VS). Selecting an optimal screening library for a specific VS ...campaign is quite important to improve the success rates and avoid wasting resources in later experimental phases. Analysis of the structural features and molecular diversity for different screening libraries can provide valuable information to the decision making process when selecting screening libraries for VS. In this study, the structural features and scaffold diversity of eleven purchasable screening libraries and Traditional Chinese Medicine Compound Database (TCMCD) were analyzed and compared. Their scaffold diversity represented by the Murcko frameworks and Level 1 scaffolds was characterized by the scaffold counts and cumulative scaffold frequency plots, and visualized by Tree Maps and SAR Maps. The analysis demonstrates that, based on the standardized subsets with similar molecular weight distributions, Chembridge, ChemicalBlock, Mucle, TCMCD and VitasM are more structurally diverse than the others. Compared with all purchasable screening libraries, TCMCD has the highest structural complexity indeed but more conservative molecular scaffolds. Moreover, we found that some representative scaffolds were important components of drug candidates against different drug targets, such as kinases and guanosine-binding protein coupled receptors, and therefore the molecules containing pharmacologically important scaffolds found in screening libraries might be potential inhibitors against the relevant targets. This study may provide valuable perspective on which purchasable compound libraries are better for you to screen.
Graphical abstract
Selecting diverse compound libraries with scaffold analyses.
Anaplastic lymphoma kinase (ALK), a tyrosine receptor kinase, has been proven to be associated with the occurrence of numerous malignancies. Although there have been already at least 3 generations of ...ALK inhibitors approved by FDA or in clinical trials, the occurrence of various mutations seriously attenuates the effectiveness of the drugs. Unfortunately, most of the drug resistance mechanisms still remain obscure. Therefore, it is necessary to reveal the bottom reasons of the drug resistance mechanisms caused by the mutations. In this work, on the basis of verifying the accuracy of 2 main kinds of binding free energy calculation methodologies end-point method of Molecular Mechanics with Poisson-Boltzmann/Generalized Born and Surface Area (MM/PB(GB)SA) and alchemical method of Thermodynamic Integration (TI), we performed a systematic analysis on the ALK systems to explore the underlying shared and specific drug resistance mechanisms, covering the one-drug-multiple-mutation and multiple-drug-one-mutation cases. Through conventional molecular dynamics (cMD) simulation in conjunction with MM/PB(GB)SA and umbrella sampling (US) in conjunction with contact network analysis (CNA), the resistance mechanisms of the in-pocket, out-pocket, and multiple-site mutations were revealed. Especially for the out-pocket mutation, a possible transfer chain of the mutation effect was revealed, and the reason why different drugs exhibited various sensitivities to the same mutation was also uncovered. The proposed mechanisms may be prevalent in various drug resistance cases.
Protein-protein interactions (PPIs) play important roles in a variety of biological processes, and many PPIs have been regarded as biologically compelling targets for drug discovery. Extensive ...efforts have been made to develop feasible proteinprotein docking approaches to study PPIs in silico. Most of these approaches are composed of two stages: sampling and scoring. Sampling is used to generate a number of plausible protein-protein binding conformations and scoring can rank all those conformations. Due to large and flexible binding interface of PPI, determination of the near native structures is computationally expensive, and therefore computational efficiency is the most challenging issue in protein-protein docking. Here, we have reviewed the basic concepts and implementations of the sampling, scoring and acceleration algorithms in some established docking programs, and the limitations of these algorithms have been discussed. Then, some suggestions to the future directions for sampling, scoring and acceleration algorithms have been proposed. This review is expected to provide a better understanding of protein-protein docking and give some clues for the optimization and improvement of available approaches.
Targeted inhibition of anaplastic lymphoma kinase (ALK) dramatically improved therapeutic outcomes in the treatment of ALK-positive cancers, but unfortunately patients invariably progressed due to ...acquired resistance mutations in ALK. Currently available drugs are all type-I inhibitors bound to the ATP-binding pocket and are most likely to be resistant in patients harboring genetic mutations surrounding the ATP pocket. To overcome drug resistance, we rationally designed a novel kind of “bridge” inhibitor, which specially bind into an extended hydrophobic back pocket adjacent to the ATP-binding site of ALK. The novel type-I1/2 inhibitors display excellent antiproliferation activity against ALK-positive cancer cells and appear superior to two clinically used drugs, crizotinib and ceritinib. Structural and molecular modeling analyses indicate that the inhibitor induces dramatic conformational transition and stabilizes unique DFG-shifted loop conformation, enabling persistent sensitivity to different genetic mutations in ALK. These data highlight a rationale for further development of next-generation ALK inhibitors to combat drug resistance.
Molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) are arguably very popular methods for binding free energy prediction since ...they are more accurate than most scoring functions of molecular docking and less computationally demanding than alchemical free energy methods. MM/PBSA and MM/GBSA have been widely used in biomolecular studies such as protein folding, protein–ligand binding, protein–protein interaction, etc. In this review, methods to adjust the polar solvation energy and to improve the performance of MM/PBSA and MM/GBSA calculations are reviewed and discussed. The latest applications of MM/GBSA and MM/PBSA in drug design are also presented. This review intends to provide readers with guidance for practically applying MM/PBSA and MM/GBSA in drug design and related research fields.
A significant number of protein-protein interactions (PPIs) are mediated through the interactions between proteins and peptide segments, and therefore determination of protein-peptide interactions ...(PpIs) is critical to gain an in-depth understanding of the PPI network and even design peptides or small molecules capable of modulating PPIs. Computational approaches, especially molecular docking, provide an efficient way to model PpIs, and a reliable scoring function that can recognize the correct binding conformations for protein-peptide complexes is one of the most important components in protein-peptide docking. The end-point binding free energy calculation methods, such as MM/GBSA and MM/PBSA, are theoretically more rigorous than most empirical and semi-empirical scoring functions designed for protein-peptide docking, but their performance in predicting binding affinities and binding poses for protein-peptide systems has not been systematically assessed. In this study, we first evaluated the capability of MM/GBSA and MM/PBSA with different solvation models, interior dielectric constants (
in
) and force fields to predict the binding affinities for 53 protein-peptide complexes. For the 19 short peptides with 5-12 residues, MM/PBSA based on the minimized structures in explicit solvent with the ff99 force field and
in
= 2 yields the best correlation between the predicted binding affinities and the experimental data (
r
p
= 0.748), while for the 34 medium-size peptides with 20-25 residues, MM/GBSA based on 1 ns of molecular dynamics (MD) simulations in implicit solvent with the ff03 force field, the GB
OBC1
model and a low interior dielectric constant (
in
= 1) yields the best accuracy (
r
p
= 0.735). Then, we assessed the rescoring capability of MM/PBSA and MM/GBSA to distinguish the correct binding conformations from the decoys for 112 protein-peptide systems. The results illustrate that MM/PBSA based on the minimized structures with the ff99 or ff14SB force field and MM/GBSA based on the minimized structures with the ff03 force field show excellent capability to recognize the near-native binding poses for the short and medium-size peptides, respectively, and they outperform the predictions given by two popular protein-peptide docking algorithms (pepATTRACT and HPEPDOCK). Therefore, MM/PBSA and MM/GBSA are powerful tools to predict the binding affinities and identify the correct binding poses for protein-peptide systems.
Determination of protein-peptide interactions is critical to gain an in-depth understanding of the protein-protein interaction network. Computational approaches, especially MM/PBSA and MM/GBSA, are powerful tools to predict the binding affinities and identify the correct binding poses for protein-peptide systems.
The identification and optimization of lead compounds are inalienable components in drug design and discovery pipelines. As a powerful computational approach for the identification of hits with novel ...structural scaffolds, structure-based virtual screening (SBVS) has exhibited a remarkably increasing influence in the early stages of drug discovery. During the past decade, a variety of techniques and algorithms have been proposed and tested with different purposes in the scope of SBVS. Although SBVS has been a common and proven technology, it still shows some challenges and problems that are needed to be addressed, where the negative influence regardless of protein flexibility and the inaccurate prediction of binding affinity are the two major challenges. Here, focusing on these difficulties, we summarize a series of combined strategies or workflows developed by our group and others. Furthermore, several representative successful applications from recent publications are also discussed to demonstrate the effectiveness of the combined SBVS strategies in drug discovery campaigns.
The identification and optimization of lead compounds are inalienable components in drug design and discovery pipelines.
Enhanced sampling has been extensively used to capture the conformational transitions in protein folding, but it attracts much less attention in the studies of protein-protein recognition. In this ...study, we evaluated the impact of enhanced sampling methods and solute dielectric constants on the overall accuracy of the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) approaches for the protein-protein binding free energy calculations. Here, two widely used enhanced sampling methods, including aMD and GaMD, and conventional molecular dynamics (cMD) simulations with two AMBER force fields (ff03 and ff14SB) were used to sample the conformations for 21 protein-protein complexes. The MM/PBSA and MM/GBSA calculation results illustrate that the standard MM/GBSA based on the cMD simulations yields the best Pearson correlation (
r
p
= −0.523) between the predicted binding affinities and the experimental data, which is much higher than that given by MM/PBSA (
r
p
= −0.212). Two enhanced sampling methods (aMD and GaMD) are indeed more efficient for conformational sampling, but they did not improve the binding affinity predictions for protein-protein systems, suggesting that the aMD or GaMD sampling (at least in short timescale simulations) may not be a good choice for the MM/PBSA and MM/GBSA predictions of protein-protein complexes. The solute dielectric constant of 1.0 is recommended to MM/GBSA, but a higher solute dielectric constant is recommended to MM/PBSA, especially for the systems with higher polarity on the protein-protein binding interfaces. Then, a preliminary assessment of the MM/GBSA calculations based on a variable dielectric generalized Born (VDGB) model was conducted. The results highlight the potential power of VDGB in the free energy predictions for protein-protein systems, but more thorough studies should be done in the future.
Enhanced sampling has been extensively used to capture the conformational transitions in protein folding, but it attracts much less attention in the studies of protein-protein recognition.
Several monoclonal antibodies targeting the programmed cell death-1/programmed cell death-ligand 1 (PD-1/PD-L1) pathway have been used successfully in anticancer immunotherapy. Inherent limitations ...of antibody-based therapies remain, however, and alternative small-molecule inhibitors that can block the PD-1/PD-L1 axis are urgent needed. Herein, we report the discovery of compound 17 as a bifunctional inhibitor of PD-1/PD-L1 interactions. 17 inhibits PD-1/PD-L1 interactions and promotes dimerization, internalization, and degradation of PD-L1. 17 promotes cell-surface PD-L1 internalized into the cytosol and induces the degradation of PD-L1 in tumor cells through a lysosome-dependent pathway. Furthermore, 17 suppresses tumor growth in vivo by activating antitumor immunity. These results demonstrate that 17 targets the PD-1/PD-L1 axis and induces PD-L1 degradation.
Abstract
Predicting the native or near-native binding pose of a small molecule within a protein binding pocket is an extremely important task in structure-based drug design, especially in the ...hit-to-lead and lead optimization phases. In this study, fastDRH, a free and open accessed web server, was developed to predict and analyze protein–ligand complex structures. In fastDRH server, AutoDock Vina and AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA free energy calculation procedures and multiple poses based per-residue energy decomposition analysis were well integrated into a user-friendly and multifunctional online platform. Benefit from the modular architecture, users can flexibly use one or more of three features, including molecular docking, docking pose rescoring and hotspot residue prediction, to obtain the key information clearly based on a result analysis panel supported by 3Dmol.js and Apache ECharts. In terms of protein–ligand binding mode prediction, the integrated structure-truncated MM/PB(GB)SA rescoring procedures exhibit a success rate of >80% in benchmark, which is much better than the AutoDock Vina (~70%). For hotspot residue identification, our multiple poses based per-residue energy decomposition analysis strategy is a more reliable solution than the one using only a single pose, and the performance of our solution has been experimentally validated in several drug discovery projects. To summarize, the fastDRH server is a useful tool for predicting the ligand binding mode and the hotspot residue of protein for ligand binding. The fastDRH server is accessible free of charge at http://cadd.zju.edu.cn/fastdrh/.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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