# Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics
## 2 Computer Simulations for Rational Drug Design
### The Swiss Knife of SBDD: Molecular Docking  
Within every SBDD campaign, available information about the target structure is exploited to fetch molecules able to recognize it selectively and potently [287]. Usually, this involves the identification of molecules that have good steric and electrostatic complementarity with the active site [288]. Depending on the steric and volumetric features of the binding site, the ligand type can be chosen accordingly, with small organic molecules being a better solution for buried cavities [289] and peptides, aptamers, or antibodies a better one for larger, flatter, and solvent-exposed interaction surfaces [290]. To narrow down the list of potentially active molecules to experimentally test to a feasible number, and to avoid wasting resources on compounds that do not possess the appropriate features to interact with the target, most SBDD campaigns start with a virtual screening process (SBVS) [291]. The most widely and successfully adopted method for SBVS is molecular docking, a computational protocol developed in the 1980s by [PERSON] et al. [292] for predicting the preferred orientation of a certain ligand within the active site of a receptor [293]. Each docking program has two major components, which cooperate to find the solution to the protein-ligand docking problem [294]. The first part is the search algorithm (SA), which explores the ligand degrees of freedom within a user-defined search space centered around the active site of the protein [295]. The SA generates several ligand conformations (poses) that are fed to the second element of the program, i.e., the scoring function (SF), which qualitatively evaluates subsisting protein-ligand interaction features [296]. In the context of the COVID-19 pandemic, docking was also the king of computational methods used for drug discovery, thanks to the combination of its accuracy [297] and rapidity, which allows it to virtually screen billions of compounds in just a few days [298, 299, 300]. For example, [PERSON] et al. reported the discovery of four low micromolar nsp13 inhibitors through a virtual screening carried out with the LiGen [301] docking program on an in-house natural compounds library [302]. [PERSON] et al. identified two micromolar SARS-CoV-2 cell-entry inhibitors that act by binding human neuropilin-1 (nrp-1) and preventing its interaction with the spike protein, by performing a virtual screening with the GOLD [303] program on a library of commercially available compounds [304]. [PERSON] et al. performed a virtual screening based on the Autodock [305] program on a library of drugs approved by the Food and Drug Administration and by the European Medical Agency (EMA) to discover six micromolar M\({}^{\text{pro}}\) inhibitors [306]. [PERSON] et al. reported the discovery of three sub-micromolar, synergistic nsp1 inhibitors identified through two independently executed virtual screenings with ICM [307, 308] and Vina [309] software on a library of FDA-approved drugs [310]. [PERSON] et al. identified 11 natural compound M\({}^{\text{pro}}\) inhibitors active in the low micromolar range through a virtual screening purely based on the commercial software Glide [311], developed by [PERSON] [312]. Another strategic use of docking-based virtual screening based on the Glide program is portrayed by the work of [PERSON] et al., which designed six mixed covalent and noncovalent nanomolar M\({}^{\text{pro}}\) inhibitors [313]. Another Glide-based virtual screening performed by [PERSON] et al. led to the repurposing of histone deacetylase (HDAC) inhibitors as SARS-CoV-2 cell entry inhibitors through allosteric modulation of ACE2 and alteration of its ability to recognize the spike protein [314]. [PERSON] et al. used LibDock [315] to perform a virtual screening on a library composed of FDA-approved peptides, which led to the identification of a nanomolar SARS-CoV-2 cell entry inhibitor that exerts its effect by binding the human ACE2 receptor [316].