PSnpBind-ML: predicting the effect of binding site mutations on protein-ligand binding affinity

Engineering affinity of humanized ScFv targeting CD147 antibody: A combined approach of mCSM-AB2 and molecular dynamics simulations

This study aims to assess the effectiveness of mCSM-AB2, a graph-based signature machine learning method, for affinity engineering of the humanized single-chain Fv anti-CD147 (HuScFvM6-1B9). In parallel, molecular dynamics (MD) simulations were used to gain valuable insights into the dynamics and affinity of the HuScFvM6-1B9-CD147 complex. The result analysis involved integrating free energy changes calculated from the mCSM-AB2 with binding free energy predictions from MD simulations. The simulated structures of the modified HuScFvM6-1B9-CD147 domain 1 complex from MD simulations were used to highlight critical residues participating in the binding surface. Interestingly, alterations in the pattern of amino acids of HuScFvM6-1B9 at the complementarity determining regions interacting with the 31EDLGS35 epitope were observed, particularly in mutants that lost binding activity. The predicted mutants of HuScFvM6-1B9 were subsequently engineered and expressed in E. coli for subsequent binding property validation. Compared to WT HuScFvM6-1B9, the mutant HuScFvM6-1B9L1:N32Y exhibited a 1.66-fold increase in binding affinity, with a KD of 1.75 × 10-8 M. While mCSM-AB2 demonstrates insignificant improvement in predicting binding affinity enhancements, it excels at predicting negative effects, aligning well with experimental validation. In addition to binding free energies, total entropy was considered to explain the discrepancy between mCSM-AB2 predictions and experimental results. This study provides guidelines and identifies the limitations of mCSM-AB2 and MD simulations in antibody engineering.

Molecular Study of Pneumocystis jirovecii in Respiratory Samples of HIV Patients in Chile

Pneumocystis is an opportunistic fungus that causes potentially fatal pneumonia (PCP) in immunocompromised patients. The objective of this study was to determine the prevalence of P. jirovecii in HIV patients through phenotypic and molecular study, to investigate the genetic polymorphisms of P. jirovecii at the mitochondrial gene mtLSU and at the nuclear dihydropteroate synthase gene (DHPS), and by analysis of molecular docking to study the effect of DHPS mutations on the enzymatic affinity for sulfamethoxazole. A PCP prevalence of 28.3% was detected, with mtLSU rRNA genotypes 3 (33.3%) and 2 (26.6%) being the most common. A prevalence of 6.7% (1/15) mutations in the DHPS gene was detected, specifically at codon 55 of the amino acid sequence of dihydropteroate synthase. Molecular docking analysis showed that the combination of mutations at 55 and 98 codons is required to significantly reduce the affinity of the enzyme for sulfamethoxazole. We observed a low rate of mutations in the DHPS gene, and molecular docking analysis showed that at least two mutations in the DHPS gene are required to significantly reduce the affinity of dihydropteroate synthase for sulfamethoxazole.

A Benchmark Study of Protein-Fragment Complex Structure Calculations with NMR2

Protein-fragment complex structures are particularly sought after in medicinal chemistry to rationally design lead molecules. These structures are usually derived using X-ray crystallography, but the failure rate is non-neglectable. NMR is a possible alternative for the calculation of weakly interacting complexes. Nevertheless, the time-consuming protein signal assignment step remains a barrier to its routine application. NMR Molecular Replacement (NMR2) is a versatile and rapid method that enables the elucidation of a protein-ligand complex structure. It has been successfully applied to peptides, drug-like molecules, and more recently to fragments. Due to the small size of the fragments, ca < 300 Da, solving the structures of the protein-fragment complexes is particularly challenging. Here, we present the expected performances of NMR2 when applied to protein-fragment complexes. The NMR2 approach has been benchmarked with the SERAPhic fragment library to identify the technical challenges in protein-fragment NMR structure calculation. A straightforward strategy is proposed to increase the method's success rate further. The presented work confirms that NMR2 is an alternative method to X-ray crystallography for solving protein-fragment complex structures.