We describe the testing and release of AutoDock4 and the accompanying graphical user interface AutoDockTools. AutoDock4 incorporates limited flexibility in the receptor. Several tests are reported here, including a redocking experiment with 188 diverse ligand-protein complexes and a cross-docking experiment using flexible sidechains in 87 HIV protease complexes. We also report its utility in analysis of covalently bound ligands, using both a grid-based docking method and a modification of the flexible sidechain technique.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.21256

AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility

Structure-based virtual screening plays an important role in drug discovery and complements other screening approaches. In general, protein crystal structures are prepared prior to docking in order to add hydrogen atoms, optimize hydrogen bonds, remove atomic clashes, and perform other operations that are not part of the x-ray crystal structure refinement process. In addition, ligands must be prepared to create 3-dimensional geometries, assign proper bond orders, and generate accessible tautomer and ionization states prior to virtual screening. While the prerequisite for proper system preparation is generally accepted in the field, an extensive study of the preparation steps and their effect on virtual screening enrichments has not been performed. In this work, we systematically explore each of the steps involved in preparing a system for virtual screening. We first explore a large number of parameters using the Glide validation set of 36 crystal structures and 1,000 decoys. We then apply a subset of protocols to the DUD database. We show that database enrichment is improved with proper preparation and that neglecting certain steps of the preparation process produces a systematic degradation in enrichments, which can be large for some targets. We provide examples illustrating the structural changes introduced by the preparation that impact database enrichment. While the work presented here was performed with the Protein Preparation Wizard and Glide, the insights and guidance are expected to be generalizable to structure-based virtual screening with other docking methods.

Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments

Given the high attrition rates, substantial costs and slow pace of new drug discovery and development, repurposing of 'old' drugs to treat both common and rare diseases is increasingly becoming an attractive proposition because it involves the use of de-risked compounds, with potentially lower overall development costs and shorter development timelines. Various data-driven and experimental approaches have been suggested for the identification of repurposable drug candidates; however, there are also major technological and regulatory challenges that need to be addressed. In this Review, we present approaches used for drug repurposing (also known as drug repositioning), discuss the challenges faced by the repurposing community and recommend innovative ways by which these challenges could be addressed to help realize the full potential of drug repurposing.

Drug repurposing: progress, challenges and recommendations

The authors describe the development and testing of a semiempirical free energy force field for use in AutoDock4 and similar grid-based docking methods. The force field is based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding. It also incorporates a charge-based method for evaluation of desolvation designed to use a typical set of atom types. The method has been calibrated on a set of 188 diverse protein-ligand complexes of known structure and binding energy, and tested on a set of 100 complexes of ligands with retroviral proteases. The force field shows improvement in redocking simulations over the previous AutoDock3 force field.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.20634

A semiempirical free energy force field with charge-based desolvation.

Molecular docking has become an increasingly important tool for drug discovery. In this review, we present a brief introduction of the available molecular docking methods, and their development and applications in drug discovery. The relevant basic theories, including sampling algorithms and scoring functions, are summarized. The differences in and performance of available docking software are also discussed. Flexible receptor molecular docking approaches, especially those including backbone flexibility in receptors, are a challenge for available docking methods. A recently developed Local Move Monte Carlo (LMMC) based approach is introduced as a potential solution to flexible receptor docking problems. Three application examples of molecular docking approaches for drug discovery are provided.

/pdf/molecular-docking-a-powerful-approach-for-structure-based-3scyz9zmai.pdf

Molecular docking: a powerful approach for structure-based drug discovery.

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches

/pdf/docking-and-scoring-in-virtual-screening-for-drug-discovery-4nrii464b0.pdf

Docking and scoring in virtual screening for drug discovery: methods and applications.

Early phase drug discovery: cheminformatics and computational techniques in identifying lead series.

The human kinome is a highly conserved target family composed of more than 500 different proteins. Kinases play fundamental roles in many intracellular pathways such as cytokinesis, cell proliferation, differentiation, and apoptosis, and are therefore implicated in various diseases. Currently there are significant efforts in therapeutic areas such as cancer and inflammation to identify novel kinase inhibitors. Random screening of a discovery compound library often results in a hit rate of 0.1 %, whereas focused library screening could improve this rate to 1 %. Consequently, libraries focused toward kinases have become starting points in screening campaigns and are complementary to conventional high-throughput screening (HTS) of discovery libraries. Compound collections catered to target families such as kinases present a unique opportunity to explore discrete chemical, biological, and property spaces. In contrast, HTS libraries are built to represent maximum diversity in the chemical and biological properties of compounds. Focused libraries are also appealing due to decreased synthesis, repository management, and screening costs. The present work describes a rapid computational process to select a collection of compounds targeted as kinase inhibitors, combining the advantages of 2D and 3D virtual screening methods for use in kinase-focused screening campaigns. In designing a general kinase screening library, the challenge lies in defining the chemical and biological space that identifies compounds with utility against any of the many possible kinase targets. Whereas some inhibitors such as staurosporine are known to be active against many kinases, others show a specific inhibitory profile. 7] The limited selectivity of many inhibitors is due to the fact that the catalytic ATP binding domain targeted is highly conserved. In recognition of the difficulty of designing selective kinase inhibitors, dualand multitarget kinase inhibitors were developed. Such “dirty drugs” (i.e. , sorefenib, sunitinib) have gained much attention in recent years and show potential to be advantageous in cancer therapy. These clinical developments have also contributed to the increased interest in general kinase inhibitor libraries. In this work, our goal was to develop a focused library selection procedure based on a 2D similarity search combined with 3D target-based filtering. A recent review argues that “2D fingerprints are surprisingly effective in many search situations in comparison with more complex 3D designs”. Indeed, 2D approaches allow a rapid analogue search from various databases. We find the combination of 2D and 3D methods has distinct advantages; it can decrease the number of false negatives, and 2D methods can represent a pre-filtering tool that enables real-time 3D virtual screening using traditional docking algorithms tailored to the evaluation of large numbers of molecules. Herein we describe our methods and characterize the general kinase-focused library.

Design, Selection, and Evaluation of a General Kinase‐Focused Library

Computational Techniques to Support Hit Triage

The present invention relates generally to compounds capable of modulating the activity of a protein serine/threonine phosphatase. The compounds can be used to treating conditions associated with protein serine/threonine phosphatase activity. The invention also relates to methods for screening compounds capable of modulating the activity of a protein serine/threonine phosphatase.

Hélène Decornez

Papers

Docking and scoring in virtual screening for drug discovery: methods and applications.

Early phase drug discovery: cheminformatics and computational techniques in identifying lead series.

Design, Selection, and Evaluation of a General Kinase‐Focused Library

Computational Techniques to Support Hit Triage

Methods and compositions for the treatment of phosphatase- related disorders