Since its first public test in 2018, Alphafold has made great strides in providing the scientific community with highly accurate AI-generated protein structure predictions. A recent database release by Alphafold contained over 200 million entries and boasts broad coverage of the UniProt protein sequence and annotation repository. Boltzmann Maps puts the power of the Alphafold database directly in the hands of users and allows for advanced analysis of protein structures.

Boltzmann Maps is pleased to introduce an integration with Pharmit as an option for pharmacophore screening. Pharmit is a search tool for finding small molecule inhibitors that bind to a target of interest. The tool searches libraries for compounds with desired features in the right geometry. Boltzmann Maps integration allows the user to send a protein-ligand system from BMaps to Pharmit for search based on the compound’s features or other user-specified features. Pharmit’s nine built-in libraries include almost 250M compound entries, and the 1,059 publicly accessible user-contributed libraries contain another 45M entries.

Pharmit can be accessed via the Export button on the bottom right of the BMaps web app.

With the new release of Boltzmann Maps comes enhanced reliability for protein structure loading and automation of protein preparation for energy minimization, docking and fragment simulations. The entirety of the Protein Data Bank (PDB) is now available to view in Boltzmann Maps. 

As an example, log into BMaps to view PDB ID 3n7h: https://www.boltzmannmaps.com/structure/3n7h. The PDB featured this mosquito odorant binding protein in complex with DEET (DE3 ligand) as one of the “Molecules of the Month” for June 2023.

The Boltzmann Maps web app now employs GPU-accelerated OpenMM software for compound energy minimization in the context of a protein. The reported energies include van der Waals and electrostatic energies between compound and protein, as well as the change of a compound’s internal energies between the unbound and bound configurations (stress). These energy reports are a key metric for evaluating and comparing compounds and modifications. OpenMM integration allows Boltzmann Maps to provide this data with improved quality and speed.

OpenMM is an open-source toolkit for molecular simulation. It is highly flexible with its custom functions and has high performance, especially on recent GPUs. More information can be found at: https://openmm.org.

Structure-based drug design starts with a compound positioned on the surface of a protein. Often, the crystal ligand in a PDB structure provides the natural starting point. But what if there is no ligand? This question took on increased urgency as the Boltzmann Maps team prepared fragment simulations on COVID-19 structures; many of the initial entries in the PDB did not have ligands. In response to this, Boltzmann Maps now provides Sample Compounds. We docked 20K+ small molecules from our libraries against hotspots on each structure and selected a handful to show in BMaps. The resulting compounds are generally commercially available, chemically diverse, and are reasonable starting points for structure-based design. They can then be used to explore new designs, using BMaps’ energy analysis and fragment data.

Sample Compounds are available for almost all of the SARS-CoV-2 structures in Boltzmann Maps. More are coming!

View a COVID-19 structure with sample compounds now >>. Or, log in to start exploring your own structure-based design modifications.

Fragment maps for ten SARS-CoV-2 virus proteins are now available in the BMaps web app to accelerate the design of COVID-19 therapeutics. These structures include the main protein protease (NSP5), the Spike protein (S), the receptor binding domain (RDB) of the S protein, and several NS (non-structural) proteins NSP3, NSP9, NSP10, NSP15, NSP16. Available for each protein are druggability sites, water molecule maps, and a starting set of 117 chemical fragment binding maps.

Start designing your COVID-19 protease inhibitors using BMaps with an expanded set of 221 fragments. The example below started with a benzimidazole fragment, then grew to a benzene-CF3 via intermediate linkers. To get started with your own possibilities, view the BMaps prepared 6LU7 structure. And stay tuned for more coronavirus structures currently in BMaps fragment simulation (6LVN, 6VSB).

To learn more about the coronavirus, visit https://www.cdc.gov/coronavirus/2019-ncov/ or https://en.wikipedia.org/wiki/Coronavirus_disease_2019.

The latest BMaps update has support for a broader set of fragment linking options when growing with fragments, significantly expanding the opportunities for compound modifications. By accessing more fragments in new sub-pockets, the new linking features provide lots of new ideas for improvements to your compounds, ranked by fragment binding scores. In addition to simple bond linking, there is now:

• methylene linking (–C– methane or single carbon);
• ethane linking (–C–C– 2 carbons);
• acetylene linking (–C≡C– 2 carbons connected by a triple bond).

The latest Boltzmann Maps enhancements make it easier to apply insights from fragment data to chemical design.

BMaps now includes visualization of fragment map summaries for each fragment map available for a given protein. Map summaries show the highest affinity (lowest chemical potential) pose of a fragment at each site on a protein where the fragment binds.  This information is useful in identifying promising scaffold fragments or new sub-pockets to exploit.