Exploration of binding sites of ligands (drug candidates) on macromolecular targets is a central question of molecular design. Although there are experimental and theoretical methods available for the determination of atomic resolution structure of drug-target complexes, they are often limited to identify only the primary binding mode (site and conformation). Systematic exploration of multiple (allosteric or prerequisite) binding modes is a challenge for present methods. The Wrapper module of our new method, Wrap 'n' Shake, answers this challenge by a fast, computational blind docking approach. Beyond the primary (orthosteric) binding mode, Wrapper systematically produces all possible binding modes of a drug scanning the entire surface of the target. In several fast blind docking cycles, the entire surface of the target molecule is systematically wrapped in a monolayer of N ligand copies. The resulted target-ligandN complex structure can be used as it is, or important ligand binding modes can be further distinguished in molecular dynamics shakers. Wrapper has been tested on important protein targets of drug design projects on cellular signaling and cancer. Here, we provide a practical description of the application of Wrapper.High-throughput computational techniques have become invaluable tools to help increase the overall success, process efficiency, and associated costs of drug development. By designing ligands tailored to specific protein structures in a disease of interest, an understanding of molecular interactions and ways to optimize them can be achieved prior to chemical synthesis. This understanding can help direct crucial chemical and biological experiments by maximizing available resources on higher quality leads. Moreover, predicting molecular binding affinity within specific biological contexts, as well as ligand pharmacokinetics and toxicities, can aid in filtering out redundant leads early on within the process. We describe a set of computational tools which can aid in drug discovery at different stages, from hit identification (EasyVS) to lead optimization and candidate selection (CSM-lig, mCSM-lig, Arpeggio, pkCSM). Incorporating these tools along the drug development process can help ensure that candidate leads are chemically and biologically feasible to become successful and tractable drugs.Quantifying discrepancies between computationally derived and native (reference) structures is an essential step in the development and comparison of protein modeling and protein-protein docking methods. Measuring conformational differences of proteins or protein complexes is also important in other areas of structural biology such as molecular dynamics and crystallography. There are multiple scores to do that. However, nearly all of them, whether superposition-based (e.g., RMSD) or superposition-free, use distances to measure similarity. CAD-score is conceptually different as it uses physical contacts represented as contact areas. Such representation makes it possible to quantify differences of both structures and surfaces (e.g., protein-protein interfaces and binding sites) using the same framework.  https://www.selleckchem.com/products/GW501516.html  A number of studies have found CAD-score to be among the most robust scores. The method is implemented both as a web server and as standalone software available at http//bioinformatics.lt/software/cad-score . Here, we describe how to use the standalone CAD-score software for comparison and analysis of protein structures, interfaces, and binding sites.The rational design of enzymes is a challenging research field, which plays an important role in the optimization of a wide series of biotechnological processes. Computational approaches allow screening all possible amino acid substitutions in a target protein and to identify a subset likely to have the desired properties. They can thus be used to guide and restrict the huge, time-consuming search in sequence space to reach protein optimality. Here we present HoTMuSiC, a tool that predicts the impact of point mutations on the protein melting temperature, which uses the experimental or modeled protein structure as sole input and is available at the dezyme.com website. Its main advantages include accuracy and speed, which makes it a perfect instrument for thermal stability engineering projects aiming at designing new proteins that feature increased heat resistance or remain active and stable in nonphysiological conditions. We set up a HoTMuSiC-based pipeline, which uses additional information to avoid mutations of functionally important residues, identified as being too well conserved among homologous proteins or too close to annotated functional sites. The efficiency of this pipeline is successfully demonstrated on Rhizomucor miehei lipase.The functional diversity of proteins is closely related to their differences in sequence and structure. Despite variations in functional sites, global structural similarity is a valuable source of information when assessing potential functional similarities between proteins. The CATH database contains a well-established hierarchical classification of more than 430,000 protein domain structures and nearly 95 million protein domain sequences, with integrated functional annotations for each represented family. The present chapter provides an overview of the main features of CATH with emphasis on exploiting structural similarities to obtain functional information for proteins.The exponential growth in the number of newly solved protein structures makes correlating and classifying the data an important task. Distance matrix alignment (Dali) is used routinely by crystallographers worldwide to screen the database of known structures for similarity to newly determined structures. Dali is easily accessible through the web server ( http//ekhidna.biocenter.helsinki.fi/dali ). Alternatively, the program may be downloaded and pairwise comparisons performed locally on Linux computers.Bio3D-web is an online application for the interactive analysis of sequence-structure-dynamics relationships in user-defined protein structure sets. Major functionality includes structure database searching, sequence and structure conservation assessment, inter-conformer relationship mapping and clustering with principal component analysis (PCA), and flexibility prediction and comparison with ensemble normal mode analysis (eNMA). Collectively these methods allow users to start with a single sequence or structure and characterize the structural, conformational, and internal dynamic properties of homologous proteins for which there are high-resolution structures available. Functionality is also provided for the generation of custom PDF, Word, and HTML analysis reports detailing all user-specified analysis settings and corresponding results. Bio3D-web is available at http//thegrantlab.org/bio3d/webapps , as a Docker image https//hub.docker.com/r/bio3d/bio3d-web/ , or downloadable source code https//bitbucket.org/Grantlab/bio3d-web .