QM-Polarized Ligand Docking software

The first such algorithm of its kind, QM-Polarized Ligand Docking uses ab initio methodology to calculate ligand charges within the protein environment. Innovative and practical, QM-Polarized Ligand Docking offers substantially enhanced accuracy over pure MM docking algorithms.

Details

Accurate treatment of electrostatic charges is crucial to the success of any docking algorithm. Although contemporary force fields are capable of modeling partial atomic charges on ligands with reasonable accuracy, they are generally incapable of considering charge polarization induced by the protein environment. The greater the role charge polarization plays in determining a ligand's bound conformation, the more difficult it will be for MM docking algorithms to perceive the correct binding mode. For research applications that demand the highest level of docking accuracy, Schrodinger introduces QM-Polarized Ligand Docking (QPLD), which uses ab inito charge calculations to overcome this limitation.

QPLD combines the docking power of Glide with the accuracy of QSite, Schrodinger's respected QM/MM software. The QPLD algorithm begins with a Glide docking job that generates several geometrically unique protein-ligand complexes. QSite then performs a single-point energy calculation on each complex, treating the ligand with ab initio methods and deriving partial atomic charges using electrostatic potential fitting. Glide then re-docks the ligand using each of the ligand charge sets calculated by QSite, and the QPLD algorithm returns the most energetically favorable pose. The fully automated algorithm is calibrated to provide useful default settings that can be modified at the user's discretion.

In keeping with Schrodinger's tradition of pairing innovation and practicality, QPLD calculations are effortlessly set up and launched using a single panel within the Maestro interface. Calculations are easily parallelized across multiple processors, and results are automatically incorporated into Maestro for visualization and analysis. 

 

Software Link: QM-Polarized Ligand Docking software

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LigPrep - Ligand Analysis Software

LigPrep goes far beyond simple 2D to 3D structure conversions by including tautomeric, stereochemical, and ionization variations, as well as energy minimization and flexible filters to generate fully customized ligand libraries that are optimized for further computational analyses.

Details

Computational methods have become an indispensable part of lead identification efforts. Nearly all methods require accurate 3D molecular models as a starting point. However, many corporate and purchasable compound databases contain only 2D molecular structures. Efficient and accurate 2D to 3D conversion is therefore a key precursor to computational analyses.

Beyond simple one-to-one structural conversion, it is equally important to generate scientifically sound molecular models that enumerate the different structural and chemical possibilities a ligand could sample, as these variations could lead to dramatically different results in subsequent computations. A versatile conversion program that can be configured to generate ligand libraries with the desired structural and chemical features can significantly streamline the entire in silico drug discovery process. 

 

Software Link: LigPrep - Ligand  Analysis Software

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Desmond - Drug design software

Desmond's combined speed and accuracy make possible long time scale molecular dynamics simulations, allowing users to examine events of great biological and pharmaceutical importance. Seamlessly integrated with Maestro, Desmond provides comprehensive setup, simulation, and analysis tools.

Details

Biological systems are dynamic in nature; analyzing their motion at the molecular and atomistic level is therefore essential to understanding key biological phenomena. For decades, there has been keen interest in modeling the dynamic aspects of protein structure and function, and molecular dynamics (MD) simulation stands alone as the fundamental computational tool for capturing dynamic events of scientific interest and pharmaceutical relevance. More recently, static structure-based approaches, such as docking and virtual screening, have made important strides in advancing drug discovery. MD, especially when coupled with these other computational tools, will open the door to addressing the many drug discovery problems for which the dynamic nature of proteins cannot be ignored, as in the mechanisms of highly mobile membrane proteins and in ligand-induced conformational changes of active sites.

Many biological phenomena of scientific and pharmaceutical interest occur on time scales that are computationally demanding to simulate. A high-performance MD code, together with continuously advancing computer hardware technologies, can be used to perform simulations on time scales that illuminate these important biological processes. Desmond, a newly developed MD code created by D. E. Shaw Research, provides an unprecedented combination of parallel scalability, simulation throughput, and scientific accuracy to achieve these goals. 

 

Software Link : Desmond - Drug design software

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Core Hopping - Ligand−Receptor Analysis Software

In addition to more conventional ligand-based methods, Core Hopping offers receptor-based scaffold hopping, exploiting information about the active site and known binding poses to guide the search for novel cores.

Details

Compounds can fail in drug development, or worse, commercially-available medications can be recalled due to unforeseen toxicity, selectivity, potency, and other unsuitable physicochemical properties. These issues can often be a function of undesirable core properties. Core hopping allows for the rapid screening of novel cores to help overcome unwanted properties by generating new lead compounds with improved core properties while preserving key R-group interactions. In addition to lead optimization, core hopping can also be valuable in idea generation for novel derivatives to a known drug.

Schrodinger's Core Hopping program not only provides the traditional ligand-based methods for exploring different scaffolds, but also offers a receptor-based method that will accurately account for detailed ligand-receptor interactions of compounds containing novel cores.

Software Link : Core Hopping - Ligand−Receptor Analysis Software

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DynaFit - Software for Biochemistry

DynaFit performs nonlinear least-squares regression of chemical kinetic, enzyme kinetic, or ligand-receptor binding data. The experimental data can be either initial reaction velocities in dependence on the concentration of varied species (e.g., inhibitor concentration vs. velocity), or the reaction progress curves (e.g., time vs. absorbance).

Details

The main purpose of the program DynaFit is to perform nonlinear least-squares regression of chemical kinetic, enzyme kinetic, or ligand-receptor binding data. The experimental data can be either initial reaction velocities in dependence on the concentration of varied species (e.g., inhibitor concentration vs. velocity), or the reaction progress curves (e.g., time vs. absorbance).

The main advantage in using the program DynaFit is in the ability to characterize the (bio)chemical reacting system in terms of symbolic, or stoichiometric, equations. For example, the ``slow, tight'' inhibition of a dissociative dimeric enzyme is described by the following text: 

 

Software Link: DynaFit - Software for Biochemistry

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CombiGlide - Ligand−Receptor Analysis Software

CombiGlide combines accurate ligand-receptor scoring, clever combinatorial docking algorithms, and highly efficient core-hopping technology to design focused libraries and identify new scaffolds. These technologies greatly facilitate lead discovery and optimization efforts.

Details
The virtual chemical space that chemists are interested in is too large to be synthesized and screened, even using modern methods of combinatorial chemistry and robotic synthesis. Therefore, there is a real need for efficient and reliable methods to rationally select the optimal library members for synthesis. Additionally, once a promising lead compound is discovered, different core scaffolds as well as side-chain substitutions must be enumerated and examined to evaluate relative binding affinities towards a particular target. Accurate ligand-receptor scoring coupled with intelligent and efficient combinatorial docking and core-hopping methods can accelerate lead optimization and aid in designing the optimal, focused compound library for further synthesis.

Schrodinger's CombiGlide can flexibly vary the core or side-chain substitutions, creating virtual combinatorial libraries that may be screened for leads, identify novel scaffolds, or generate focused libraries in support of lead optimization efforts.

Software Link: CombiGlide - Ligand−Receptor Analysis Software

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Liaison - Ligand−Receptor Analysis Software

Liaison applies linear interaction approximation to accurately compute binding affinities for series of ligands with similar binding modes, making it a powerful tool for lead optimization.
Details
Accurate ranking of binding affinities is crucial in the lead optimization phase of pharmaceutical research in order to develop potent, effective drug candidates. Both academic groups and the pharmaceutical industry have invested a great deal of effort to meet this challenge. Several approaches have been developed, ranging from rapid QSAR-based scoring functions to computationally intensive free energy perturbation (FEP) calculations. But none have fully met the needs of researcher and developers. QSAR-type approaches, though rapid, involve many approximations and produce large errors in binding energy predictions. FEP approaches are more accurate, but cannot be used when ligand structures vary significantly. They also incur substantial CPU costs.

Linear interaction approximation (LIA) is a way of combining molecular mechanics calculations with experimental data to build a model scoring function for the evaluation of ligand-protein binding free energies. LIA methods strike a perfect balance between accuracy and computational cost.

Software Link : Liaison - Ligand−Receptor Analysis Software

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ConfGen - Ligand−Receptor Analysis Software

Reproducing bioactive ligand geometries in minimally sized conformer sets, accurate results from high-performance ConfGen calculations save time and effort in downstream applications.

Details
Conformer generation is useful in many aspects of both molecular modeling in general and drug discovery in particular. The relative energies of small molecule conformations play a crucial role in determining shape, function, and activity. Moreover, the ability to generate a bioactive conformer is a vital pre-requisite to any successful computer-aided drug design project.

While it's impossible for a conformer search algorithm to determine a flexible ligand's bioactive conformer with absolute confidence, carefully considered search criteria do allow an algorithm to reject conformers likely to be high energy or inactive. Beyond merely expediting the conformer search process, this approach creates efficiently sized conformer sets that nevertheless contain a reasonable approximation of the bioactive geometry.

Efficient conformer sets have wide-ranging ramifications in downstream applications. For example, with fewer irrelevant conformations to process, virtual database screens and shape-based similarity searches run to completion in a fraction of the time without sacrificing accuracy.

Software Link: ConfGen - Ligand−Receptor Analysis Software

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QSite - Drug design software

QSite applies quantum mechanics to the reactive center of a protein active site and molecular mechanics to the rest of the system. Its accuracy allows detailed understanding of reactions involving proteins, making it a powerful tool for lead optimization.

Details
Insight into reactive chemistry is crucial to understanding the mechanism of drug receptor interactions in systems where the ligand is covalently bound to the receptor. For example, it's necessary to study the transition states between bound and unbound forms in order to design antibiotics that are not subject to inactivation by beta lactamases. Classical molecular mechanics (MM) methods cannot describe the electronic changes during a reaction, and are ill-equipped to address ligand-receptor interactions in systems containing metals.

Ab initio quantum mechanics (QM) is required to study reactive chemistry or interactions involving transition metals in a protein environment. However, even with today's computer technology, full QM calculations of entire proteins are still intractable.

Mixed QM/MM calculations provide the ideal solution by separating out the reactive core, which can be accurately described with QM, while treating the remainder of the complex more efficiently with MM. While QM/MM may not be needed for every structure-based drug design project, many important systems cannot be effectively addressed by any other computational means. QM/MM is therefore a key component in the arsenal of computational drug discovery.

Software Link : QSite - Drug design software

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SiteMap - Ligand−Receptor Analysis Software

Combining a novel algorithm for rapid binding site identification and evaluation with easy-to-use property visualization tools, SiteMap provides researchers with an efficient means to find and better exploit the characteristics of ligand binding sites.

Details
Understanding the structure and exploiting the function of protein active sites is a cornerstone of drug design. Doing so requires chemists to know the location of these sites, yet at the outset of many drug design projects the location of a binding site for protein-ligand or protein-protein interactions remains unknown. Additionally, it is equally important to identify the locations of any potential allosteric binding sites.

SiteMap's proven algorithm for binding site identification and evaluation can help researchers to locate binding sites with a high degree of confidence and predict the druggability of those sites. Beyond lead discovery, SiteMap assists in lead optimization by providing insight into ligand-receptor interactions so as to suggest effective strategies to modify lead compounds to enhance receptor complementarity.

Software Link: SiteMap - Ligand−Receptor Analysis Software

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Induced Fit - Ligand−Receptor Analysis Software

The active site geometry of a protein complex depends heavily upon conformational changes induced by the bound ligand. However, resolving the crystallographic structure of a protein-ligand complex requires a substantial investment of time, and is frequently infeasible or impossible. Schrodinger's Induced Fit (IFD) protocol solves this problem by using Glide and Prime to exhaustively consider possible binding modes and the associated conformational changes within receptor active sites. The unique procedure allows chemists to quickly predict active site geometries with minimal expense, even for systems as challenging as hERG homology models.

The Induced Fit protocol begins by docking the active ligand with Glide. In order to generate a diverse ensemble of ligand poses, the procedure uses reduced van der Waals radii and an increased Coulomb-vdW cutoff, and can temporarily remove highly flexible side chains during the docking step. For each pose, a Prime structure prediction is then used to accommodate the ligand by reorienting nearby side chains. These residues and the ligand are then minimized. Finally, each ligand is re-docked into its corresponding low energy protein structures and the resulting complexes are ranked according to GlideScore. Accuracy is ensured by Glide's superior scoring function and Prime's advanced conformational refinement.

The Induced Fit methodology has been thoroughly refined in real-world research applications, and is readily used by novice and expert modelers alike. Maestro, the graphical user interface for all Schrodinger software, allows researchers to easily perform Induced Fit simulations and interpret the results. In addition to default settings suitable for a wide range of systems, the Induced Fit interface features advanced options that can be customized to solve more challenging cases. Calculations can be completed in a matter of hours on a desktop machine, or in as few as 30 minutes when distributed across multiple processors.

Software Link : Induced Fit - Ligand−Receptor Analysis Software

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