AlphaKnot 2.0: a web server for the visualization of proteins' knotting and a database of knotted AlphaFold-predicted models.

The availability of 3D protein models is rapidly increasing with the development of structure prediction algorithms. With the expanding availability of data, new ways of analysis, especially topological analysis, of those predictions are becoming necessary. Here, we present the updated version of the AlphaKnot service that provides a straightforward way of analyzing structure topology.

Slipknotted and unknotted monovalent cation-proton antiporters evolved from a common ancestor.

While the slipknot topology in proteins has been known for over a decade, its evolutionary origin is still a mystery. We have identified a previously overlooked slipknot motif in a family of two-domain membrane transporters. Moreover, we found that these proteins are homologous to several families of unknotted membrane proteins.

Knot_pull-python package for biopolymer smoothing and knot detection.

Summary: The biggest hurdle in studying topology in biopolymers is the steep learning curve for actually seeing the knots in structure visualization. Knot_pull is a command line utility designed to simplify this process-it presents the user with a smoothing trajectory for provided structures (any number and length of protein, RNA or chromatin chains in PDB, CIF or XYZ format), and calculates the knot type (including presence of any links, and slipknots when a subchain is specified).

Availability And Implementation: Knot_pull works under Python >=2.

PconsFam: An Interactive Database of Structure Predictions of Pfam Families.

At present, about half of the protein domain families lack a structural representative. However, in the last decade, predicting contact maps and using these to model the tertiary structure for these protein families have become an alternative approach to gain structural insight. At present, reliable models for several hundreds of protein families have been created using this approach.

DCA-MOL: A PyMOL Plugin To Analyze Direct Evolutionary Couplings.

Direct coupling analysis (DCA) is a statistical modeling framework designed to uncover relevant molecular evolutionary relationships from biological sequences. Although DCA has been successfully used in several applications, mapping and visualizing of evolutionary couplings and direct information to a particular set of molecules requires multiple steps and could be prone to errors. DCA-MOL extends PyMOL functionality to allow users to interactively analyze and visualize coevolutionary residue-residue interactions between contact maps and structures.

GapRepairer: a server to model a structural gap and validate it using topological analysis.

Motivation: Over 25% of protein structures possess unresolved fragments. On the other hand, approximately 6% of protein chains have non-trivial topology (and form knots, slipknots, lassos and links). As the topology is fundamental for the proper function of proteins, modeling of topologically correct structures is decisive in various fields, including biophysics, biotechnology and molecular biology.

LinkProt: a database collecting information about biological links.

Protein chains are known to fold into topologically complex shapes, such as knots, slipknots or complex lassos. This complex topology of the chain can be considered as an additional feature of a protein, separate from secondary and tertiary structures. Moreover, the complex topology can be defined also as one additional structural level.