Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

Allostery plays a key role in the regulation of the activity and function of many biomolecules. And although many ligands act through allostery, no systematic use is made of it in drug design strategies. Here we describe a procedure for identifying the regions of a protein that can be used to control its activity through allostery. This procedure is based on the construction of a plausible conformational path, which describes protein transition between known active and inactive conformations. The path is calculated by using a framework approach that steers and markedly improves the conjugate peak refinement method. The evolution of conformations along this path was used to identify a putative allosteric site that could regulate activation of Bacillus anthracis adenylyl cyclase toxin (EF) by calmodulin. Conformations of the allosteric site at different steps along the path from the inactive (free) to the active (bound to calmodulin) forms of EF were used to perform virtual screenings and propose candidate EF inhibitors. Several candidates then proved to inhibit calmodulin-induced activation in an in vitro assay. The most potent compound fully inhibited EF at a concentration of 10 μM. The compounds also inhibited the related adenylyl cyclase toxin from Bordetella pertussis (CyaA). The specific homology between the putative allosteric sites in both toxins supports that these pockets are the actual binding sites of the selected inhibitors.

Protein conformation has been recognized as the key feature determining biological function, as it determines the position of the essential groups specifically interacting with substrates. Hence, the shape of the cavities or grooves at the protein surface appears to drive those functions. However, only a few studies describe the geometrical evolution of protein cavities during molecular dynamics simulations (MD), usually with a crude representation. To unveil the dynamics of cavity geometry evolution, we developed an approach combining cavity detection and Principal Component Analysis (PCA). This approach was applied to four systems subjected to MD (lysozyme, sperm whale myoglobin, Dengue envelope protein and EF-CaM complex). PCA on cavities allows us to perform efficient analysis and classification of the geometry diversity explored by a cavity. Additionally, it reveals correlations between the evolutions of the cavities and structures, and can even suggest how to modify the protein conformation to induce a given cavity geometry. It also helps to perform fast and consensual clustering of conformations according to cavity geometry. Finally, using this approach, we show that both carbon monoxide (CO) location and transfer among the different xenon sites of myoglobin are correlated with few cavity evolution modes of high amplitude. This correlation illustrates the link between ligand diffusion and the dynamic network of internal cavities.

Effective drugs against SARS-CoV-2 are urgently needed to treat severe cases of infection and for prophylactic use. The main viral protease (nsp5 or 3CLpro) represents an attractive and possibly broad-spectrum target for drug development as it is essential to the virus life cycle and highly conserved among betacoronaviruses. Sensitive and efficient high-throughput screening methods are key for drug discovery. Here we report the development of a gain-of-signal, highly sensitive cell-based luciferase assay to monitor SARS-CoV-2 nsp5 activity and show that it is suitable for the screening of compounds in a 384-well format. A benefit of miniaturisation and automation is that screening can be performed in parallel on a wild-type and a catalytically inactive nsp5, which improves the selectivity of the assay. We performed molecular docking-based screening on a set of 14,468 compounds from an in-house chemical database, selected 359 candidate nsp5 inhibitors and tested them experimentally. We identified two molecules which show anti-nsp5 activity, both in our cell-based assay and in vitro on purified nsp5 protein, and inhibit SARS-CoV-2 replication in A549-ACE2 cells with EC₅₀ values in the 4–8 μM range. The here described high-throughput-compatible assay will allow the screening of large-scale compound libraries for SARS-CoV-2 nsp5 inhibitors. Moreover, we provide evidence that this assay can be adapted to other coronaviruses and viruses which rely on a viral protease.

Identifying druggable cavities on a protein surface is a crucial step in structure based drug design. The cavities have to present suitable size and shape, as well as appropriate chemical complementarity with ligands.